Systems/techniques that facilitate deep learning image analysis with increased modularity and reduced footprint are provided. In various embodiments, a system can access medical imaging data. In various aspects, the system can perform, via execution of a deep learning neural network, a plurality of inferencing tasks on the medical imaging data. In various instances, the deep learning neural network can comprise a common backbone in parallel with a plurality of task-specific backbones. In various cases, the plurality of task-specific backbones can respectively correspond to the plurality of inferencing tasks.
Various methods and systems are provided for an imaging system including a an X-ray source generating X-rays; an X-ray detector positioned opposite of the X-ray source for receiving X-rays; a gantry rotatably positioned within a gantry enclosure; a gantry motor coupled to the gantry to rotate the gantry; a power distribution unit (PDU) coupled to the gantry to provide power to the gantry; and a boost converter circuitry coupled to the PDU to maintain a voltage output of the PDU during generation of X-rays by the X-ray source. The method of providing power, via the PDU, to a gantry motor to rotate the gantry; providing power, via the PDU, to the X-ray source; and activating the boost converter circuitry to provide a voltage regulation to the gantry motor rotating the gantry via a gantry motor drive at a constant rotational speed.
H05G 1/10 - Power supply arrangements for feeding the X-ray tube
H02J 9/04 - Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting in which the distribution system is disconnected from the normal source and connected to a standby source
3.
SYSTEM AND METHOD FOR GENERATING DENOISED SPECTRAL CT IMAGES FROM SPECTRAL CT IMAGE DATA ACQUIRED USING A SPECTRAL CT IMAGING SYSTEM
Various systems and methods are provided for denoising spectral CT image data, the system and method comprising determining a denoised linear estimation of spectral CT image data by maximizing or minimizing a first objective function, wherein at least one parameter of the denoised linear estimation is determined by at least one machine learning system. The denoiser is based on a Linear Minimum Mean Square Error (LMMSE) estimator. The LMMSE is very fast to compute, but not commonly used for CT image denoising, due to its inability to adapt the amount of denoising to different parts of the image and the difficulty to derive accurate statistical properties from the CT image data. To overcome these problems, a model-based deep learning model, such as a deep neural network that preserves a model based LMMSE structure.
The present discussion relates to structures and devices to facilitate application of an ultrasound therapy beam (106) to a target anatomic region in a replicable manner. In certain aspects, an alignment controller (30) may be used to analyze images generated by an ultrasound transducer. The alignment controller (30) may then send a communication to indicate the energy application device is positioned to provide therapy to the target region, or if the device needs to be repositioned. The alignment control of the energy application device provides guided repeatable targeting of the target anatomic region, even when in non-clinical settings.
Various methods and systems are provided for generating super-resolution images. In one embodiment, a method comprises: progressively up-sampling an input image to generate a super-resolution output image by: generating N intermediate images based on the input image, where N is equal to at least one, including a first intermediate image by providing the input image to a deep neural network, where a resolution of the first intermediate image is a multiple of a resolution of the input image, higher than the resolution of the input image, and can be any positive real value and not necessarily an integer value; generating the super-resolution output image based on the N intermediate images, the super-resolution output image having a resolution higher than a respective resolution of each intermediate image of the N intermediate images and the resolution of the input image; and displaying the super-resolution output image via a display device.
Various methods and systems are provided for predicting a discharge date of a patient of a healthcare facility. In one embodiment, a method for a patient management system of a healthcare facility comprises receiving a selected confidence level from a user of the patient management system; predicting a date for discharging a patient of the healthcare facility using a trained discharge date prediction model, based on a set of patient data of the patient, the discharge date prediction model trained on historical patient data of the healthcare facility; based on the received confidence level and an output of the trained discharge date prediction model, predict a discharge date window of the patient; generating a predicted discharge date window element summarizing the discharge window prediction in a user interface (UI) of the patient management system; and displaying the UI on a display device of the patient management system.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
G16H 70/20 - ICT specially adapted for the handling or processing of medical references relating to practices or guidelines
7.
DYNAMIC MULTIMODAL SEGMENTATION SELECTION AND FUSION
Techniques are described that facilitate dynamic multimodal segmentation selection and fusion in medical imaging. In one example embodiment, a computer processing system receives a segmentation dataset comprising a combination of different image segmentations of an anatomical object of interest respectively segmented via different segmentation models from different medical images captured of the (same) anatomical object, wherein the different medical images and the different image segmentations vary with respect to at least one of, capture modality, acquisition protocol, or acquisition parameters. The system employs a dynamic ranking protocol as opposed to a static ranking protocol to determine ranking scores for the different image segmentations that control relative contributions of the different image segmentations in association with combining the different image segmentations into a fused segmentation for the anatomical object. The system further combines the different image segmentations based on the ranking scores to generate the fused image segmentation.
Methods and systems are provided for automating steps of a workflow within a medical image processing system. In one example, a method for a medical image processing system comprises extracting expressions from description fields of a set of Digital Imaging and Communications in Medicine (DICOM) files of a medical imaging exam that match reference terms of an ontology; mapping the matching reference terms of the ontology to one or more lexicon entries of a radiology lexicon; selecting a suitable software application to review the medical imaging exam based on the one or more lexicon entries; opening the suitable software application on a device of the medical image processing system; and displaying the medical imaging exam on a display of the device within the suitable software application. The ontology includes reference terms generated from DICOM sources, vocabulary from other relevant lexicons, ontologies, reference databases, and human experts.
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 40/60 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
G16H 30/00 - ICT specially adapted for the handling or processing of medical images
9.
METRIC-BASED DATA MANAGEMENT FOR X-RAY IMAGING SYSTEMS
An X-ray imaging system includes a gantry with moving and stationary parts. The parts are communicatively coupled via a data communication system. The moving part includes an X-ray source that emits X-rays; an X-ray detector configured to generate detector data; and on-moving-gantry processing circuitry. The on-moving-gantry processing circuitry is configured to determine, for each of a number of partial data sets of the generated detector data, a metric value of at least one metric, the metric value being translatable into a type of data management for the partial data set among at least two different types of data management. The on-moving-gantry processing circuitry is further configured to decide, for each partial data set, how the partial data set is to be treated based on the determined metric value of the at least one metric and to selectively effectuate data management according to the corresponding type of data management.
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
Systems/techniques that facilitate automated training of machine learning classification for patient missed care opportunities or late arrivals are provided. In various embodiments, a system can access a set of annotated data candidates defined by two or more feature categories. In various aspects, the system can train a machine learning classifier on the set of annotated data candidates, thereby causing internal parameters of the machine learning classifier to become iteratively updated. In various instances, the system rank the two or more feature categories in order of classification importance, based on the iteratively updated internal parameters of the machine learning classifier. In various cases, the system can perform one or more electronic actions based on the two or more feature categories being ranked in order of classification importance.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
Various methods and systems are provided for automatically classifying a plurality of image slices using body region bounding boxes identified from a localizer image. In one embodiment, a localizer image may be mapped to a plurality of bounding boxes, corresponding to a plurality of body regions, using a trained machine learning model. Coordinates of the plurality of bounding boxes may be used to determine body region boundaries, such that the body regions are non-intersecting and coherent. The body regions identified in the localizer image may then be correlated to image slice ranges, and image slices within each image slice range may be labeled as belonging to the corresponding body region.
An anesthesia control system (105). The anesthesia control system (105) is configured to: acquire a plurality of physiological parameters of a patient (110); acquire anesthetic parameters of a plurality of anesthesia devices (102, 103) acting on the patient (110); acquire an anesthesia depth index of the patient (110); and automatically generate a control instruction on the basis of the plurality of physiological parameters, the anesthetic parameters, the anesthesia depth index, and a target anesthesia depth index, the control instruction being used for controlling the anesthetic parameters of each of the plurality of anesthesia devices (102, 103), so that the anesthesia depth index of the patient (110) is adjusted to the target anesthesia depth index. Also provided are an anesthesia system (100) and a non-transitory computer readable medium.
A61M 16/01 - Devices for influencing the respiratory system of patients by gas treatment, e.g. mouth-to-mouth respiration; Tracheal tubes specially adapted for anaesthetising
A61M 5/172 - Means for controlling media flow to the body or for metering media to the body, e.g. drip meters, counters electrical or electronic
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
Techniques are described that facilitate online monitoring of clinical data streams in association with detecting missing data and other suspicious data deviations. According to an embodiment, a computer implemented comprises receiving, by a system comprising a processor, a data stream from a plurality of different clinical data information systems configured to report defined clinical events within the data stream and recording arrival times of received events of the defined clinical events. The method further comprises detecting, by the system, data failure events associated with the data stream based on time differences between the arrival times for defined clinical events of the same type and estimated probabilities that the time differences are expected, wherein the detecting comprises estimating the probabilities that the time differences are expected using time-to-event models developed for each of the defined clinical events of the same type.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G06N 20/10 - Machine learning using kernel methods, e.g. support vector machines [SVM]
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
14.
GENERALIZABLE MACHINE LEARNING MEDICAL PROTOCOL RECOMMENDATION
THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY OFFICE OF THE GENERAL (USA)
Inventor
Pal, Debashish
Shen, Yaxi
Nichols, Steven
Singh, Ravi Raj
Ciano, Amanda
Choudhury, Arindam Dutta
Langlotz, Curt
Loening, Andreas
Chaudhari, Akshay
Bahrami, Naeim
Abstract
An architecture and techniques for providing a generalizable machine learning recommendation in connection with medical protocols such as radiology protocols. In response to receipt of a medical examination order request in a standardized input format, the system can, based on a machine learning technique, output a recommended protocol according to a standardized output format. The system can then perform a mapping procedure that maps site-specific data to the standardized input format and the standardized output format. The site-specific data can comprise information that is specific to an entity that provides the medical examination order request.
Systems and techniques that facilitate management of network settings of imaging protocols are provided. In an embodiment, a system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise an input component that receives network management input, and a network settings management component that manages network settings of one or more protocols of a protocol library associated with one or more imaging devices of an organization remotely via an imaging protocol manager based on the network management input.
Imaging protocol conflict management systems and methods (e.g., using a computerized tool) are enabled. For example, a system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise a conflict component that, according to a defined conflict criterion and based on a comparison of one or more medical device protocols associated with a medical device and one or more library protocols associated with a protocol library, determines a protocol conflict, and an output component that renders an output representative of the protocol conflict.
A system and method for reviewing imaging protocols in an imaging protocol management system is described herein. An example system includes processors and storage devices in a cloud and a cloud-based imaging protocol manager leveraging the processors and the storage devices. The imaging protocol manager includes a library for storing imaging protocols and a review module configured to review and standardize the imaging protocols stored in the library. The system also includes a user interface device having a web browser-based application to access imaging protocols stored in the library. The web browser-based application enables creation, editing, and review of the imaging protocols stored in the library. The imaging protocols are approved using the web browser-based application prior to being published in the library, and a plurality of imaging systems. The plurality of imaging systems accesses the imaging protocols from the library.
THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY (USA)
Inventor
Pal, Debashish
Chaudhari, Akshay
Loening, Andreas
Shokrollahi, Peyman
Zambrano Chaves, Juan Manuel
Shen, Yaxi
Doraiswamy, Vignesh
Prasad, Raghu
Dhareshwar, Supreeth
Bahrami, Naeim
Abstract
Various methods and systems are provided for automatically recommending one or more radiology protocols based on an imaging examination order which includes both structured and unstructured data. In one example, a method includes receiving an imaging examination order requesting an imaging examination, wherein the imaging examination order comprises structured data and unstructured text, converting the unstructured text into one or more feature vectors, mapping the structured data and the one or more feature vectors to a standardized radiology protocol representation using an imaging examination order classifier, and mapping the standardized radiology protocol representation to a site- specific radiology protocol using a site-specific radiology protocol translator.
Systems and methods are provided for workload management in a healthcare setting. In one example, a method for determining a workload demand of a medical facility includes automatically determining a workload score for a care team including plurality of clinicians over a shift based on shift data and event data received from the medical facility, including calculating a cumulative workload over the shift based on the event data and a workload reduction over time based on the shift data, generating a graphical workload score tile including a visual representation of the workload score, arranging the graphical workload score tile in a workload graphical user interface (GUI), and displaying the GUI on a display device.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G06Q 10/0631 - Resource planning, allocation, distributing or scheduling for enterprises or organisations
G06Q 10/1093 - Calendar-based scheduling for persons or groups
G06Q 10/0639 - Performance analysis of employees; Performance analysis of enterprise or organisation operations
20.
MEDICAL DEVICES HAVING MODIFIABLE FUNCTIONALITY AND METHODS OF MANAGING MEDICAL DEVICE FUNCTIONALITY VIA APPLICATIONS
A medical device(20) for a patient. The medical device(20) includes a memory system(CS120) configured to store available applications(60). A computing system(CS100) is configured to execute the available applications(60) stored in the memory system(CS120), where each of the available applications(60) corresponds toa function performed via the medical device(20). An applications management module(50) is executable by the computing system(CS100) to add an additional application to the available applications(60) stored in the memory system(CS120), where subsequent execution of the additional application by the computing system(CS100) causes the medical device(20) to perform the function correspondingthereto. A display device(22) is configured to display the available applications(60) stored in the memory system(CS120) that are available for execution.
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
21.
MEDICAL DEVICES AND METHODS FOR PRESENTING CARDIAC INFORMATION FOR PATIENT
A method (200) for presenting cardiac information (27) originating from multiple leads (L) connected to a patient (2). The method (200) includes receiving the cardiac information (27) collected via the multiple leads (L, 202) and detecting a segment within the cardiac information (27, 204). The method (200) further includes creating a radar chart (40) divided into sectors (42, 206) and plotting data points (50) on the radar chart (40) that correspond to the cardiac information (27) for first and second sets (52, 54) of leads (L) within the multiple leads (L), where the data points (50) corresponding to the first set (52) of leads (L) are shown differently than the data points (50) corresponding to the second set (54) of leads (L) so as to be visually distinguishable from each other (208).
A medical device (20) for a patient (2) including a computing system configured to generate time series data for the patient. A display device (22) is configured to display the time series data generated by the computing system. An annotation module is executable by the computing system and configured to receive an annotation input. The annotation input includes an event time, where the annotation module is configured to time-associate the event time with the time series data and to display a time-based annotation at the event time along with the time series data. The annotation input is provided as at least one of a user input and an automated trigger. A memory system is configured to store the time series data generated by the computing system and the time-based annotation for subsequent display on the display device (22).
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
23.
SYSTEMS AND METHODS FOR IMPROVED INTERRUPTION AND RESUMPTION MANAGEMENT
Interruptions of user activity can cost time and money for organizations. Improved technology is needed for interruption and resumption management. A communication engine can monitor the task state of a user, receive an incoming matter, analyze the incoming matter with a classification model, compare the analyzed incoming matter with the priority of the task state of the user, and interrupt the user by providing the incoming matter to the user if the priority of the analyzed incoming matter is greater than the priority of the task state of the user. When the user would like to resume their interrupted task, the communication engine can provide an output refocus communication and automatically return the device software status to the task state of the user when the interruption occurred.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
THE BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY (USA)
Inventor
Gilat-Schmidt, Tal
Grönberg, Fredrik
Sjölin, Martin
Fan, Jiahua
Thomsen, Brian, W.
Thibault, Jean-Baptiste
Hsieh, Jiang
Danielsson, Mats
Yang, Yirong
Pelc, Norbert
Wang, Adam, S.
Abstract
Methods and systems are provided for downsampling detector data in a computed tomography imaging system. In an example, a method for a photon-counting computed tomography (PCCT) system includes, during a scan of an imaging subject, obtaining detector data from a photon-counting detector of the PCCT system, the detector data comprising, for each pixel or detector element of the photon-counting detector, photon counts partitioned into a plurality of energy bins based on an energy imparted by each photon on the photon-counting detector, applying a bin factor to the plurality of energy bins for each pixel to downsample the plurality of energy bins into a reduced number of energy bins, and reconstructing one or more images from the reduced number of energy bins.
G01N 23/046 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or by transmitting the radiation through the material and forming images of the material using tomography, e.g. computed tomography [CT]
G01T 1/166 - Scintigraphy involving relative movement between detector and subject
G06T 5/10 - Image enhancement or restoration by non-spatial domain filtering
25.
METHODS AND SYSTEMS FOR IMPLEMENTING AND USING DIGITAL IMAGING AND COMMUNICATIONS IN MEDICINE (DICOM) STRUCTURED REPORTING (SR) OBJECT CONSOLIDATION
Systems and methods for implementing and using digital imaging and communications in medicine (DICOM) structured reporting (SR) object consolidation. The consolidation process may be applied to a plurality of objects generated based on a same medical imaging data. The consolidation process includes assessing each object of the plurality of objects, with the assessing including determining whether the object is a parent of another object in the plurality of objects, and discarding the object when it is a parent of another object. A composite object is then generated based on the plurality of objects, with the generating including, when only one object remains after the assessing, copying that object into the consolidated object; otherwise when a plurality of remaining objects remains after the assessing, processing the remaining objects, in sequence from newest to oldest, with the processing including, for copying each data element in each remaining object into the composite object.
Various methods and systems are provided for display of recommended treatment based on a patient's medical history and standardized guidelines. In one example, a computing system includes a display screen configured to display a patient medical path listing one or more of treatment guidelines and patient medical history, and to display abbreviated representations of at least one of the treatment guidelines and the patient medical history that can be reached directly from the displayed patient medical path. The abbreviated representations each display a limited list of data that is selectable to launch the treatment guidelines and/or the patient medical history and enable the selected data to be seen.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 70/20 - ICT specially adapted for the handling or processing of medical references relating to practices or guidelines
27.
METHODS AND SYSTEMS FOR LONGITUDINAL PATIENT INFORMATION PRESENTATION
Various methods and systems are provided for longitudinal presentation of patient information. In one example, a computing device (102) comprises a display screen (134), the computing device (102) being configured to display on the screen (134) a timeline (200, 300, 400) of patient medical information including a plurality of symbols representing the patient medical information, wherein a symbol of the plurality of symbols is selectable to launch a details panel (222) and enable a report that references the displayed patient medical information to be seen within the timeline, and wherein the symbol is displayed while the details panel is in an un-launched state.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
28.
SYSTEMS AND METHODS TO REDUCE UNSTRUCTURED AND STRUCTURED NOISE IN IMAGE DATA
The current disclosure provides methods and systems to reduce an amount of structured and unstructured noise in image data. Specifically, a multi-stage deep learning method is provided, comprising training a deep learning network using a set of training pairs interchangeably including input data from a first noisy dataset with a first noise level and target data from a second noisy dataset with a second noise level, and input data from the second noisy dataset and target data from the first noisy dataset; generating an ultra-low noise data equivalent based on a low noise data fed into the trained deep learning network; and retraining the deep learning network on the set of training pairs using the target data of the set of training pairs in a first retraining step, and using the ultra-low noise data equivalent as target data in a second retraining step.
Various systems and methods for managing disposable sensors and electrode gel are disclosed. According to an embodiment, a sensor assembly configured to be attached to a patient includes one or more electrode modules. Each of the one or more electrode modules includes an electrode, electrode gel disposed in a storage location on the electrode module, wherein electrode gel is not in contact with the electrode in the storage location, and a deformable cap configured to move the electrode gel from the storage location into contact with the electrode in response to a deformation of the deformable cap.
A61B 5/1468 - Measuring characteristics of blood in vivo, e.g. gas concentration, pH-value using chemical or electrochemical methods, e.g. by polarographic means
A61B 5/145 - Measuring characteristics of blood in vivo, e.g. gas concentration, pH-value
The present disclosure relates to a C-shaped arm for use with a medical imaging system. In accordance with certain embodiments, the C-shaped arm comprises a C-shaped portion, a radiation source carried by the C-shaped portion, and a radiation detector carried by the C-shaped portion, wherein at least a portion of the C-shaped portion is formed of a unidirectional ultra-high modulus carbon fiber material.
An ultrasound imaging device or probe (106) includes a tip (134) having a heat conducting exterior housing (136) within which an imaging element (180) is positioned. The imaging element (180) is engaged with a heat sink (190) formed of an electrically insulating material that also has high thermal conductivity. The heat sink (190) contacts and extends through and electrically insulating enclosure (142) within which the imaging element (180) is disposed. As a result, the heat generated by the imaging element (180) can be readily conducted to the ambient environment via the heat sink (190) and heat conductive exterior housing (136) while also enabling the imaging element (180) and other electrical components to be electrically insulated from the housing (136).
Systems and methods for patient history analysis and time-line segmentation are provided. The method comprises acquiring health records of a patient using a plurality of medical devices over a duration of treatment. The health records comprise at least one action or an event related to the patient and storing the health records in electronic format. The method further comprises identifying beginning and end of at least one action or the event related to the patient using a begin-end marker detection module and mark the beginning and end boundary of at least one action or the event. The method further comprises segmenting the at least one action or the event by generating ambiguous timeline boundaries of the at least one action or the event using a segment begin-end detection module. The method further comprises demarcating the segment boundaries and arranging the segments in order of timeline.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
33.
DATA DIVERSITY VISUALIZATION AND QUANTIFICATION FOR MACHINE LEARNING MODELS
Systems and techniques that facilitate data diversity visualization and/or quantification for machine learning models are provided. In various embodiments, a processor can access a first dataset and a second dataset, where a machine learning (ML) model is trained on the first dataset. In various instances, the processor can obtain a first set of latent activations generated by the ML model based on the first dataset, and a second set of latent activations generated by the ML model based on the second dataset. In various aspects, the processor can generate a first set of compressed data points based on the first set of latent activations, and a second set of compressed data points based on the second set of latent activations, via dimensionality reduction. In various instances, a diversity component can compute a diversity score based on the first set of compressed data points and second set of compressed data points.
Systems and methods are provided for new data storage and management scheme for medical imaging solutions. Medical data storage and management processes, including at least a separation process and a recovery process, may be applied to a medical dataset. The separation process includes identifying blob data elements in the medical dataset, moving data of the identified blob data elements into corresponding separated data objects, and generating data for indicating the moving of data of and for tracking location of moved data of the identified blob data elements. The recovery process includes identifying removed blob data elements in a separated medical dataset, with data of the identified removed blob data elements moved into corresponding separated data objects, and for each identified removed blob data element determining, based on corresponding separation data, location of a corresponding separated data object; and retrieving, based on determined location, data of the removed blob data element.
Techniques are described for computer-aided diagnostic evaluation of liver exams. A method embodiment comprises rendering, by a system operatively coupled to a processor, medical images of a liver of a patient in a graphical user interface (GUI) of a medical imaging application that facilitates evaluating liver imaging exams. The method further comprises identifying, by the system, an observation on the liver as depicted in one or more of the medical images and evaluating defined imaging features associated with the observation as depicted in the one or more medical images. The method further comprises providing, by the system, feature information regarding the defined imaging features via the GUI.
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
36.
SYSTEM AND METHODS FOR INFERRING THICKNESS OF OBJECT CLASSES OF INTEREST IN TWO-DIMENSIONAL MEDICAL IMAGES USING DEEP NEURAL NETWORKS
Methods and systems are provided for inferring thickness and volume of one or more object classes of interest in two-dimensional (2D) medical images, using deep neural networks. In an exemplary embodiment, a thickness of an object class of interest may be inferred by acquiring a 2D medical image, extracting features from the 2D medical image, mapping the features to a segmentation mask for an object class of interest using a first convolutional neural network (CNN), mapping the features to a thickness mask for the object class of interest using a second CNN, wherein the thickness mask indicates a thickness of the object class of interest at each pixel of a plurality of pixels of the 2D medical image; and determining a volume of the object class of interest based on the thickness mask and the segmentation mask.
Systems and methods are provided for utilizing histogram views for improved visualization of three-dimensional (3D) medical images. Imaging data obtained during medical imaging examination of a patient may be processed, with the imaging data corresponding to a particular medical imaging technique. At least one medical image may be generated based on processing of the imaging data. Histogram data may be generated based on the at least one medical image. At least one histogram may be displayed along with the at least one medical image or a projection of the at least one medical image, with the at least one histogram including or being is based on the histogram data, and with the at least one histogram being displayed next to and aligned with the at least one medical image or the projection of the at least one medical image.
Various methods and systems are provided for determining a quality of a medical gas flow. In one example, a method for a medical gas quality monitoring system includes obtaining measurements of a medical gas via a plurality of sensors, the plurality of sensors including at least one of a humidity sensor, a particulate matter sensor, a carbon dioxide sensor, and a total volatile organic compound (tVOC) sensor, determining a gas quality index of the medical gas based on the obtained measurements, and outputting the determined gas quality index.
An infant care device that can include a failure indicating feature in one or more of the side panels to discourage improper use of the side panels to move the infant care device. When a side panels is used to move the infant care device and a force greater than a pre-determined maximum is applied to the side panel, the failure indicting feature indicates such improper use. The failure indicating feature is designed to provide an indication at a level of force that is less than the level of force that would damage the hinge and latch assembly holding the side panel. The failure indicating feature can provide a physical indication or a visual indication when a force greater than a predetermined maximum is applied to the side panel.
Embodiments for adjusting a setting are described herein. In some examples, a system can include a processor that can detect a setting selection with a user interface displayed with a touchscreen display device and generate a modified setting menu to be displayed with the user interface, wherein the modified setting menu comprises at least an adjusted setting value and a cancel indicator, wherein the cancel indicator provides a current setting value. The processor can also determine whether a confirmation selection confirms the adjusted setting value and, if so, modify the setting based on the confirmation selection. The processor can also determine whether a cancellation selection of the cancel indicator is detected and, if so, close the modified setting menu without adjusting the setting.
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
G06F 3/0488 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
Intelligent, distributed medical software management (e.g., using a computerized tool) is enabled. A system can comprise a processor, and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising determining requirement information representative of one or more requirements of a medical application off a group of medical applications, wherein the medical application is associated with a medical device, based on the requirement information, allocating elements of a cluster employable to host and run the medical application in a medical application container, wherein the elements of the cluster are determined to satisfy the requirement information, and in response to allocating the elements of the cluster, hosting the medical application in the medical application container, wherein hosting the medical application comprises communicatively coupling the medical application to the medical device.
A sensing device for acquiring data via a finger. The device includes a wrap having a central portion with a tip wing, a first side wing, and a second side wing each extending therefrom. The wrap has an exterior side and an opposite finger side that faces towards the finger. An electronics system is coupled to the wrap and has a sensor configured to acquire the data from the finger. An adhesive is configured to adhere the sensing device to the finger. First and second attachment portions are positioned on finger side of the first side wing and on the exterior side of the second side wing, respectively, where the first and second attachment portions removably attach to each other to non-adhesively secure the wrap around the finger.
A61B 5/145 - Measuring characteristics of blood in vivo, e.g. gas concentration, pH-value
A61B 5/1455 - Measuring characteristics of blood in vivo, e.g. gas concentration, pH-value using optical sensors, e.g. spectral photometrical oximeters
A sensing device for acquiring data from a finger. The device includes a carrier board having a stacked portion with a finger side and a canopy side. A tip wing extends from the stacked portion and wraps around the finger. Electrical components are coupled to the carrier board, including a first circuit board on the canopy side of the stacked portion, and one or more optical components electrically on the tip wing. The optical components are configured to transmit light towards the finger and to detect the light from the finger. The carrier board electrically couples the electrical components to acquire the data from the finger. A power system is positioned between the canopy side and the finger side of the carrier board, where the power system provides power to the electrical components via the carrier board. A cover secures the carrier board to the finger.
A61B 5/1455 - Measuring characteristics of blood in vivo, e.g. gas concentration, pH-value using optical sensors, e.g. spectral photometrical oximeters
A61B 5/0205 - Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
A ventilator system includes a gas flow chamber configured to receive ventilation gas circulating in a ventilation gas pathway of the ventilator and at least one UVC lamp. The UVC lamp is configured to radiate UVC spectrum light into the gas flow chamber to inactivate pathogens in the ventilation gas. A flow sensor is configured to measure a gas flow rate of the ventilation gas and a controller is configured to receive the gas flow rate, determine an intensity based on the gas flow rate, and control power to the UVC lamp based on the intensity.
A method for making a container for retaining anesthetic agent. The method includes creating two or more parts each having a mating surface, where the container is formed when the mating surfaces of the two or more parts are coupled together, and where a first part of the two or more parts is formed of a material having pores defined within the mating surface thereof. The method further includes processing the mating surface of the first part via friction stir welding to reduce the pores defined therein. The method further includes coupling the two or more parts together such that the mating surfaces contact to create the container configured to retain the anesthetic agent therein.
A61J 1/14 - Containers specially adapted for medical or pharmaceutical purposes - Details; Accessories therefor
A61M 16/01 - Devices for influencing the respiratory system of patients by gas treatment, e.g. mouth-to-mouth respiration; Tracheal tubes specially adapted for anaesthetising
A61M 19/00 - Devices for local anaesthesia; Devices for hypothermia
B23K 1/00 - Soldering, e.g. brazing, or unsoldering
B23K 20/12 - Non-electric welding by applying impact or other pressure, with or without the application of heat, e.g. cladding or plating the heat being generated by friction; Friction welding
Techniques are described for generating mono-modality training image data from multi-modality image data and using the mono-modality training image data to train and develop mono-modality image inferencing models. A method embodiment comprises generating, by a system comprising a processor, a synthetic 2D image from a 3D image of a first capture modality, wherein the synthetic 2D image corresponds to a 2D version of the 3D image in a second capture modality, and wherein the 3D image and the synthetic 2D image depict a same anatomical region of a same patient. The method further comprises transferring, by the system, ground truth data for the 3D image to the synthetic 2D image. In some embodiments, the method further comprises employing the synthetic 2D image to facilitate transfer of the ground truth data to a native 2D image captured of the same anatomical region of the same patient using the second capture modality.
Systems and method for detecting malfunctioning display devices are disclosed herein. In one example, a display device for providing information can include a sensor to detect verification data indicating one or more display characteristics of display device output, and a processor to detect a set of configuration images to display using the display device. The processor can also display each configuration image from the set of configuration images and receive verification data from the sensor, wherein the verification data indicates the one or more display characteristics of the display device output. The processor can also determine that the verification data received by the sensor proximate to the display device does not match at least one of the configuration images from the set of configuration images and provide an alert indicating the display device is malfunctioning.
G09G 3/00 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes
G02F 1/13 - Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour based on liquid crystals, e.g. single liquid crystal display cells
Provided in the present invention are an optimization method and system for a medical system, and a computer-readable storage medium. The method comprises: setting a plurality of virtual examination targets and a plurality of virtual nodes, wherein the plurality of virtual nodes separately have an initial quantity of virtual resources; controlling the plurality of virtual examination targets to sequentially pass through the plurality of virtual nodes to simulate a plurality of actual examination phases in a medical examination procedure; and in the process of simulation, determining a node to be optimized in the plurality of virtual nodes based on a current simulation result, and adjusting the quantity of virtual resources of the node to be optimized.
Systems and methods are provided for wirelessly obtaining a physiological signal from a patient. In one embodiment, a system comprises a plurality of sensors spaced apart from one another and adapted to measure physiological signals from a patient, and a communication module configured to wirelessly transmit the physiological signals measured by the plurality of sensors to a computing device. In this way, a fabric cover with the plurality of sensors and the communication module integrated therein may be washable and/or disposable while also enabling acquisition of an ECG signal and/or heart rate for neonatal or infant care applications.
A thermal management system and method for cooling a CT detector assembly of a CT imaging system. The thermal management system uses a combination of air cooling for the readout electronics of the CT detector assembly and liquid cooling for the X-ray sensors of the CT detector assembly. The hybrid air and liquid cooling systems and methods may be coupled together in the thermal management system and method to create a cooler temperature in the CT detector assembly. The CT detector assembly components may include CT detector modules, which may include X-ray sensors, readout electronics and other components.
Various methods and system are provided for cleaning a touchscreen display that is part of a medical device. In one example, a method includes entering a cleaning mode in response to a user input, receiving cleaning touch inputs through the touchscreen display while in the cleaning mode, and graphically representing an area of the touchscreen display that has been contacted with the cleaning touch inputs in real-time while in the cleaning mode to illustrate the area of the touchscreen display that has been cleaned.
G06F 3/0488 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G06F 3/041 - Digitisers, e.g. for touch screens or touch pads, characterised by the transducing means
G06F 3/048 - Interaction techniques based on graphical user interfaces [GUI]
G16H 40/40 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
H04M 1/17 - Hygienic or sanitary devices on telephone equipment
52.
SYSTEMS AND METHODS FOR RESPIRATORY SUPPORT RECOMMENDATIONS
Methods and systems are provided for generating respiratory support recommendations. In one embodiment, a method includes extracting imaging features from patient imaging information for a patient, extracting non-imaging features from patient clinical data of the patient, entering the imaging features and the non-imaging features to a joint model trained to output respiratory support recommendations as a function of the imaging features and the non-imaging features, and displaying one or more respiratory support recommendations output by the joint model.
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
A61B 5/08 - Measuring devices for evaluating the respiratory organs
G16H 50/80 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
An infant warming system includes a bassinet having a platform configured to support an infant, at least one wireless physiological sensor configured to measure a physiological parameter from the infant and transmit physiological parameter data, and at least two radio frequency identification (RFID) readers. The RFID readers are configured to communicate with the at least one wireless physiological sensor to facilitate pairing therewith so as to enable receipt of the physiological parameter data from the wireless physiological sensors at the infant warmer system. The RFID readers each have a range distance that is less than a length of the platform and are positioned such that the wireless physiological sensor is in the range distance of at least one of the at least two RFID readers from any location on the platform.
Various methods and systems are provided for X-ray imaging. In one embodiment, In one embodiment, a method includes acquiring an initial computed tomography (CT) image volume and an initial X-ray image of a subject, acquiring a subsequent X-ray image of the subject, generating a synthetic baseline X-ray image from the initial CT image volume according to the initial X-ray image, and outputting the synthetic baseline X-ray image and the subsequent X-ray image for comparison. In this way, X-ray images acquired at different times and different projection angles may be directly compared, thereby enabling a radiologist to monitor changes in imaged structures over time.
A physiological sensor includes a sensing element to detect physiological information from a patient's skin, a substrate configured to hold the sensing element on the patient's skin, and at least two contact probes on the substrate. The contact probes are positioned on the substrate such that galvanically contact the patient's skin when the substrate is fully attached against the patient's skin. A controller is configured to measure impedance between the at least two contact probes and determine whether the substrate has lifted from the patient's skin based on the impedance.
Techniques regarding the management of computational resources based on clinical priority associated with one or more computing tasks are provided. For example, one or more embodiments described herein can regard a system comprising a memory that can store computer-executable components. The system can also comprise a processor, operably coupled to the memory, that executes the computer-executable components stored in the memory. The computer-executable components can include a prioritization component that can prioritize computer applications based on a clinical priority of tasks performed by the computer applications. The clinical priority can characterize a time sensitivity of the tasks. The computer-executable components can also include a resource pool component that can divide computational resources across a plurality of resource pools and can assign the computer applications to the plurality of resource pools based on the clinical priority.
G16H 10/00 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data
G16H 70/00 - ICT specially adapted for the handling or processing of medical references
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
57.
SYSTEMS AND METHODS FOR DYNAMIC SELECTION OF SENSORS FOR OBTAINING PHYSIOLOGICAL DATA FROM A PATIENT
Various methods and systems are provided for selecting sensors for acquiring physiological data of a patient. In one embodiment, a system comprises a plurality of sensors, a dynamic selection switch communicatively coupled to the plurality of sensors, a plurality of acquisition channels communicatively coupled to the dynamic selection switch, and a processor communicatively coupled to the dynamic selection switch and configured with executable instructions in non-transitory memory that when executed cause the processor to: select a subset of sensors; control the dynamic selection switch to connect the subset of sensors to the plurality of acquisition channels; and acquire, from the subset of sensors via the plurality of acquisition channels, physiological data of a patient. In this way, a subset of sensors in a plurality of sensors may be dynamically selected in real-time for acquiring physiological data of the patient.
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A neonatal blanket includes a substrate material configured to cover a neonate and at least one antenna on the substrate material, where the antenna is configured to transmit RF energy to power the at least one wireless physiological sensor on the neonate. The blanket further includes a power connection configured to connect to a power source to power the wireless physiological sensor via the antennae.
A method for optimizing deep learning model performance using image harmonization as a pre-processing step comprises decomposing, by a system operatively coupled to a processor, an input image into sub-images. The method further comprises harmonizing the sub-images with corresponding reference sub-images of at least one reference image based on two or more different statistical values respectively calculated for the sub-images and the corresponding reference-sub images, resulting in transformation of the sub-images into modified sub-images images. The modified sub-images can be combined into a harmonized image having a more similar appearance to the at least one reference image relative to the input image. Harmonized images and/or modified sub-images generated using these techniques can be used as ground-truth training samples for training one or more deep learning model to transform input images with appearance variations into harmonized images.
Systems and methods are provided herein for remotely controlling a life-critical medical device. In one example, a system includes a life-critical medical device communicatively coupled to a remote device and configured to supply a medical therapy to a patient, the life-critical medical device including a display and memory storing instructions executable to output, to the display, a graphical user interface (GUI) that displays a plurality of real-time machine settings of the life-critical medical device, responsive to a first user input, display, via the GUI, a remote control panel including a session code usable to authenticate the remote device, and responsive to receiving an indication from an access server that the remote device has been authenticated, display, on the GUI, a notification indicating that the life-critical medical device is currently controlled by the remote device.
A61M 16/00 - Devices for influencing the respiratory system of patients by gas treatment, e.g. mouth-to-mouth respiration; Tracheal tubes
A61M 16/10 - Preparation of respiratory gases or vapours
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 20/40 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
61.
SYSTEMS AND METHODS FOR DETERMINING PATIENT DISEASE LOAD
Systems and methods are provided for collecting, aggregating, and visualizing resource availability information including patient disease load for one or more medical facilities. In one example, a method includes determining, based on one or more test results of one or more tests for a disease included in a data stream from a medical facility and further based on an amount of time since the one or more tests were conducted, whether a patient suspected of having the disease is positive, negative, or under investigation for the disease; and updating one or more resource availability graphical user interfaces (GUIs) based on the determination.
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 70/00 - ICT specially adapted for the handling or processing of medical references
G06F 3/0481 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
A method of processing ECG data includes generating a first feature set with a trained neural network using ECG data and processing a patient's ECG data using a criteria-based algorithm to generate a second feature set. The patient's ECG data is then clustered into a number of clusters based on the first feature set and the second feature set to generate clustered ECG data. The clustered ECG data is presented to a user via a user interface, and user input is received from the user via the user interface regarding the clustered ECG data. A feature vector is defined based on the user input and the feature vector is applied to at least a portion of the patient's ECG data to generate revised clustered ECG data. The revised clustered ECG data is then presented to the user via the user interface.
Various methods and systems are provided for ultrasound imaging. In one embodiment, a method comprises acquiring, with an ultrasound transducer of a scanning apparatus during an ultrasound scan of a patient, an ultrasound image, detecting, with an artificial intelligence model, a region of interest within the ultrasound image including a possible tumor, acquiring, with the ultrasound transducer, an elastic image of tissue within the region of interest, and displaying, with a display device, the elastic image. In this way, shear wave elastography may be automatically targeted to a region of interest, thereby reducing the processing load for the analysis and enabling a higher elasticity imaging frame rate for three-dimensional ultrasound imaging.
A capacitive transducer comprising a top electrode and a bottom electrode, and a sidewall between the top electrode and the bottom electrode. The sidewall is configured to separate the top electrode and the bottom electrode by a gap. There is a high contact resistance part on one or both of a bottom side of the top electrode or a top side of the bottom electrode.
A system for identifying healthcare assets includes a set of tags configured to communicate with one another, the set of tags including a root tag configured to transmit an asset identifier identifying the healthcare asset and a plurality of component tags each configured to transmit a component identifier identifying a component of the healthcare asset. A receiver system is configured to receive the asset identifier and the plurality of component identifiers from the set of tags and to automatically generate a bill of materials (BOM) for the healthcare asset based on the asset identifier and the plurality of component identifiers.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 40/40 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
66.
METHODS AND SYSTEMS FOR USING THREE-DIMENSIONAL (3D) MODEL CUTS BASED ON ANATOMY FOR THREE-DIMENSIONAL (3D) PRINTING
Systems and methods are provided for three-dimensional (3D) printing with three-dimensional (3D) model cuts based on anatomy, in particular during medical imaging operations.
A method of monitoring a patient includes operating a first wireless sensing device to measure at least first physiological parameter from a patient and wirelessly transmit a first parameter data based on the first physiological measurements. The first parameter data is received at a first patient monitor from the wireless sensing devices. First physiological information is then displayed on a first display associated with the first patient monitor, wherein the first physiological information is based on the parameter data. The first wireless sensing device is detected in a predefined area associated with a second patient monitor and identification information of the first wireless sensing devices is then communicated to the second patient monitor. The second patient monitor is then operated to receive the first parameter data from the first wireless sensing device and to display the first physiological information on a second display associated with the second patient monitor.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
68.
SYSTEMS AND METHODS FOR WIRELESSLY PAIRING MEDICAL DEVICES USING NON-NUMERIC KEY PATTERNS
A method for wirelessly pairing a medical acquisition device and a host device. The method includes requesting an authentication key associated with the medical acquisition device to be entered into the host device, and producing a key pattern on the medical acquisition device representative of the authentication key, where the key pattern is non-numeric. The method further includes providing a plurality of targets on the host device, and receiving selections of the plurality of targets to form an entry pattern on the host device. The method further includes wirelessly pairing the medical acquisition device and the host device only when the entry pattern is determined to match the key pattern on the medical acquisition device.
A backing panel (210) for a transducer (204) of an ultrasound scanner probe (200), comprising a core layer (214) sandwiched by a first skin layer (212a) and a second skin layer (212b). The transducer may comprise a front portion and a rear portion, where the front portion points to a direction of a target for the ultrasound scanner probe, and the first skin layer is adjacent to the rear portion of the transducer.
A61B 8/00 - Diagnosis using ultrasonic, sonic or infrasonic waves
B06B 1/00 - Processes or apparatus for generating mechanical vibrations of infrasonic, sonic or ultrasonic frequency
G10K 11/00 - Methods or devices for transmitting, conducting or directing sound in general; Methods or devices for protecting against, or for damping, noise or other acoustic waves in general
70.
OPTIMIZING PATIENT PLACEMENT AND SEQUENCING IN A DYNAMIC MEDICAL SYSTEM USING A COMPLEX HEURISTIC WITH EMBEDDED MACHINE LEARNING
Techniques for optimizing patient placement and sequencing in dynamic medical environment. In various embodiments, a method includes receiving current state information regarding a current state of a medical facility system in real-time, including operating conditions data regarding current operating conditions of the medical facility system and patient case data regarding active patient cases and pending patient cases of the medical facility system. It further includes forecasting future state information for the medical facility system based on the current state information using a machine learning framework, including forecasted timeline information regarding future timing of workflow events of the active patient cases and pending patient cases. It further includes employing a heuristic-based optimization mechanism to determine optimal reactive solutions regarding patient sequencing, patient placement and resource allocation based on the current state information, the future state information, rules of the medical care facility system, and one or more optimization criteria.
Various methods and systems are provided for a multi-frequency transducer array. In one example, the transducer array includes an element formed of one or more sub- elements, at least one sub-element having a different resonance frequency. A frequency range of the transducer array may thereby be broadened.
G01H 11/08 - Measuring mechanical vibrations or ultrasonic, sonic or infrasonic waves by detecting changes in electric or magnetic properties by electric means using piezoelectric devices
B06B 1/06 - Processes or apparatus for generating mechanical vibrations of infrasonic, sonic or ultrasonic frequency making use of electrical energy operating with piezoelectric effect or with electrostriction
72.
METHOD AND SYSTEM FOR SYNCHRONIZING MEDICAL IMAGE ANALYSIS AND REPORTING
Systems and methods for synchronizing medical image analysis and reporting are provided. The method includes receiving an examination type selection. The method includes selecting a viewing context (e.g., hanging protocol and/or image analysis tools) applied by an image viewer to medical images based on the examination type selection. The method may include selecting a reporting template based on the examination type selection. The method includes receiving a user analysis input (e.g., measurement and/or annotation) with reference to one of the medical images presented via the image viewer at a display system according to the viewing context. The method includes generating and presenting an image object having the user analysis input in the medical image via the image viewer at the display system. The method includes generating a report object corresponding to the image object. The report object includes the user analysis input and is inserted in the reporting template
Various methods and systems are provided for a multi-frequency transducer array. In one example, ground recovery in the transducer array is enabled by configuring an acoustic stack of the transducer array with an interdigitated structure, a top layer coupled to a front side of the interdigitated structure, and a bottom layer coupled to a back side of the interdigitated structure, where the top layer and the bottom is electrically continuous with the interdigitated structure.
B06B 1/06 - Processes or apparatus for generating mechanical vibrations of infrasonic, sonic or ultrasonic frequency making use of electrical energy operating with piezoelectric effect or with electrostriction
H01L 41/083 - Piezo-electric or electrostrictive elements having a stacked or multilayer structure
74.
METHODS AND SYSTEMS FOR MULTI-FREQUENCY TRANSDUCER ARRAY FABRICATION
Various methods and systems are provided for a multi-frequency transducer array. In one example, the transducer array is fabricated by forming an interdigitated structure from a first comb structure with a first sub-element and a second comb structure with a second sub-element. The interdigitated structure is coupled to a base package, a matching layer, and a backing layer to form a plurality of multi-frequency transducers.
B06B 1/06 - Processes or apparatus for generating mechanical vibrations of infrasonic, sonic or ultrasonic frequency making use of electrical energy operating with piezoelectric effect or with electrostriction
75.
ALGORITHM ORCHESTRATION OF WORKFLOWS TO FACILITATE HEALTHCARE IMAGING DIAGNOSTICS
Techniques for orchestrating execution of algorithms on medical images according to pre-defined workflows and techniques for managing workflow and model execution are provided. In an embodiment, a system comprises a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components comprise an algorithm catalog that comprises algorithm information identifying algorithms available for processing medical images, the algorithm information comprising algorithm execution instructions for executing the algorithms as web-services; and an onboarding component that adds the algorithm information to the algorithm catalog in response to reception of the algorithm information via an onboarding user interface of an algorithm management application, wherein based on inclusion of the algorithm information in the algorithm catalog, the algorithms are made available for incorporating into workflows for executing the algorithms on the medical images.
The present disclosure relates to leveraging machine algorithms to help guide users to effortlessly assign the correct protocol for an exam order using a standard protocol library and patient clinical information, and it further automates the scanner protocol selection creating a seamless workflow. This helps to reduce time on protocoling, and ensure the right exam is delivered for the patient in an efficient manner. In accordance with certain embodiments, a method includes receiving, with a processor, an order for a medical imaging procedure, wherein the medical imaging procedure corresponds to a patient, in response to receding receiving the physician order, obtaining, via the processor, medical information stored in an information technology system, wherein the medical information relates to the patient, and automatically generating, with the processor, a medical imaging protocol as a function of the obtained medical information.
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
77.
SYSTEM AND METHOD FOR AUTOMATIC GENERATION OF A THREE-DIMENSIONAL POLYGONAL MODEL WITH COLOR MAPPING FROM A VOLUME RENDERING
Systems and methods are provided for automatically generating a three-dimensional (3D) polygonal model with color mapping from a volume rendering. The method includes generating a volume rendering from volumetric data. The method includes receiving a user selection to launch model and color generation. The method includes automatically generating a 3D mask from the volume rendering by segmenting at least one object in the volume rendering in response to the user selection. The method includes automatically generating a 3D mesh for the at least one object based on the 3D mask in response to the user selection. The method includes automatically computing mesh colors based on the volume rendering in response to the user selection. The mesh colors are applied to the 3D mesh to generate a multi-color 3D polygonal model. The method includes automatically outputting the multi-color 3D polygonal model in response to the user selection.
Systems and methods for providing information to a caregiver, including displaying with an interface real-time data for a patient receiving care from the caregiver, and providing access to a results database configured to store results data for the patient. The method further includes determining whether a test for the patient is pending, where upon completion of the test a test result from the test is stored among the results data in the results database. The method further includes displaying, when the test is determined to be pending, a visual indicator on the interface in addition to the real-time data, where the visual indicator provides the information to the caregiver that the test is pending and that the test result corresponding thereto will be accessible via the results database only after the test is completed.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 40/60 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
79.
RESPIRATORY GAS SENSOR SYSTEM WITH COLOR DETECTION
A gas analyzer for measuring a respiratory gas component includes an emitter that transmits infrared (IR) radiation through a measurement chamber containing respiration gas, and at least one IR detector configured to receive at least a portion of the IR radiation transmitted through the measurement chamber and to generate radiation measurement data based on the received IR radiation. A light source is configured to emit light onto a color indicator, wherein the color indicator is one of a predefined set of colors. A color detector is configured to detect light reflected by a color indicator so as to identify color information. The controllers configured to determine a respiratory gas component concentration within the measurement chamber based on the color information and the radiation measurement data.
Methods and systems are provided for automatically diagnosing a patient based on a reduced lead electrocardiogram (ECG), using one or more deep neural networks. In one embodiment, a method for automatically diagnosing a patient using a reduced lead ECG comprises, acquiring reduced lead ECG data, wherein the reduced lead ECG data comprises less than twelve lead signals, determining a type of each of the less than twelve lead signals, selecting a deep neural network based on the type of each of the less than twelve lead signals, and mapping the less than twelve lead signals to a diagnosis using the deep neural network. In this way, reduced lead ECG data may be mapped to a diagnosis using an intelligently selected deep neural network, wherein the deep neural network was trained on reduced lead ECG data comprising a same set of ECG lead types as the acquired reduced lead ECG data.
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
81.
SYSTEMS AND METHODS FOR ELECTROCARDIOGRAM DIAGNOSIS USING DEEP NEURAL NETWORKS AND RULE-BASED SYSTEMS
Methods and systems are provided for automatically diagnosing an electrocardiogram (ECG) using a hybrid system comprising a rule-based system and one or more deep neural networks. In one embodiment, by mapping ECG data to a plurality of features using a convolutional neural network, mapping the plurality of features to a preliminary diagnosis using a decision network, and determining a diagnosis based on the ECG data and the preliminary diagnosis using the rule-based system, a more accurate diagnosis may be determined. In another example, by incorporating both a rule-based system and one or more deep neural networks into the hybrid system, the hybrid system may be more easily adapted for use in various contexts/communities, as the one or more deep learning networks may be trained using context/community specific ECG data.
A system and method to reduce and manage patient monitoring alarms utilizing a longitudinal, analytics-based analysis. The method includes a patient monitoring system receiving monitored data from one or more patients and generating threshold alerts for each patient based upon alert thresholds in real time. The number of alert thresholds that occur over an analysis period is compared to an enhanced alert threshold. If the number and frequency of the threshold alerts violates an enhanced alert threshold, an enhanced indicator is generated on a display for the patient being monitored. The enhanced indicator can be generated for any one or multiple monitored data types from the patient and enhances the longitudinal monitoring of the patient over an analysis period. The enhanced indicator provides a visual indicator to the monitoring technician of the occurrence of a higher than desired number of threshold alerts over the analysis period.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
G06F 3/01 - Input arrangements or combined input and output arrangements for interaction between user and computer
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
83.
RESPIRATORY GAS ANALYZER AND A BEAM SPLITTER THEREFOR
A gas analyzer for measuring a respiratory gas component includes an emitter that emits two different wavelengths of infrared (IR) radiation in to a measurement chamber containing a respiratory gas, wherein the two different wavelengths include a first IR wavelength and a second IR wavelength. The gas analyzer further includes a first IR detector, a second IR detector, and a beam splitter. The beam splitter is configured to receive the two different wavelengths of radiation emitted by the emitter and to split the two wavelengths of radiation so as to reflect the first IR wavelength to the first IR detector and reflect the second IR wavelength to the second IR detector.
G01N 21/3504 - Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing gases, e.g. multi-gas analysis
G02B 27/00 - Optical systems or apparatus not provided for by any of the groups ,
G01N 21/31 - Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
G01N 33/497 - Physical analysis of biological material of gaseous biological material, e.g. breath
84.
SYSTEMS AND METHOD FOR AN OPTICAL ANESTHETIC AGENT LEVEL SENSOR
Systems and methods are provided for anesthetic agent level sensing. In one embodiment, a system for a level sensor for an anesthetic vaporizer includes a measurement tube (302) including a float (304) positioned therein, a bottom portion of the measurement tube coupled to a cap (306) having a central opening, a retaining bracket coupled to a top portion of the measurement tube, an optical sensor housed within the retaining bracket, the optical sensor (318) including a light source positioned to emit light toward an interior of the measurement tube and a light detector positioned to receive light from the interior of the measurement tube, and an optical window housed within the retaining bracket and coupled between the optical sensor and the interior of the measurement tube.
A61M 16/01 - Devices for influencing the respiratory system of patients by gas treatment, e.g. mouth-to-mouth respiration; Tracheal tubes specially adapted for anaesthetising
A61M 16/10 - Preparation of respiratory gases or vapours
G01D 5/26 - Mechanical means for transferring the output of a sensing member; Means for converting the output of a sensing member to another variable where the form or nature of the sensing member does not constrain the means for converting; Transducers not specially adapted for a specific variable using optical means, i.e. using infrared, visible or ultraviolet light
85.
METHODS AND SYSTEMS FOR COMPUTER-AIDED DIAGNOSIS WITH DEEP LEARNING MODELS
Various methods and systems are provided for computer-aided diagnosis. In one embodiment, a method comprises acquiring, with an imaging system, a medical image of a subject, generating, with a radiologist model associated with a radiologist of an institution, a computer-aided diagnosis for the medical image, the radiologist model comprising a deep neural network trained on a plurality of diagnoses provided by the radiologist, displaying, to the radiologist via a display device, the medical image and the computer-aided diagnosis, and selectively updating, based on the medical image, one or more of the radiologist model, an institution model associated with the institution, and a geographic model associated with a geographic area containing the institution. In this way, a radiologist may be assisted by a deep neural network model configured as a digital twin of the radiologist.
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
86.
APPARATUS AND METHODS OF MONITORING MATERNAL AND FETAL HEART RATE
Systems and methods of maternal and fetal monitoring include acquiring ultrasound physiological data with an ultrasound transducer. A plurality of electrodes acquire biopotential physiological data from the skin of a patient. A controller receives the ultrasound and biopotential physiological data and calculates fetal heart rate (fHR) values, maternal heart rate (mHR) values, and uterine activity (UA) values from the ultrasound and biopotential physiological data.
Systems and methods are provided for perioperative care in a medical facility. In an example, a system includes a display and a computing device operably coupled to the display and storing instructions executable to output, to the display, a graphical user interface (GUI) that includes real-time medical device data determined from output of one or more medical devices each monitoring a patient, and where at least some of the real-time medical device data displayed via the GUI is displayed as a plurality of patient monitoring parameter tiles, each patient monitoring parameter tile showing a most-recently determined value or a trend for that patient monitoring parameter, the plurality of patient monitoring parameter tiles arranged according to a first layout; and responsive to a user action, adjust one or more patient monitoring parameter tiles of the plurality of patient monitoring parameter tiles to form a second layout.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
In an example, a system includes a computing device storing instructions executable to: receive an insight defined by a user, the insight dictating that a notification be output when a condition and a scope of the condition are met, the condition and the scope defined by the user; receive real-time medical device data determined from output from a plurality of medical devices monitoring a plurality of patients; determine if a set of values of one or more patient monitoring parameters of the medical device data meet the condition and the scope, and if so, output the notification for display on a display operably coupled to a first care provider device associated with the user; and responsive to a request from the user, adjust a privacy setting of the insight to allow the insight to be distributed to one or more additional care provider devices associated with other users.
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
89.
SYSTEMS AND METHODS FOR GRAPHICAL USER INTERFACES FOR MEDICAL DEVICE TRENDS
Systems and methods are provided for perioperative care in a medical facility. In an example, a system includes a display and a computing device operably coupled to the display and storing instructions executable to output, to the display, a graphical user interface (GUI) that includes a plurality of trend lines each showing values for a respective patient monitoring parameter over a first time range, the plurality of trend lines time-aligned and vertically stacked relative to each other, responsive to a first user input, adjust each of the plurality of trend lines to show values for the respective patient monitoring parameter over a second time range, and responsive to a second user input, display, on the GUI, an overlay that shows a relative change in each patient monitoring parameter over a specified time duration.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
90.
ANNOTATION PIPELINE FOR MACHINE LEARNING ALGORITHM TRAINING AND OPTIMIZATION
Techniques are provided for enhancing the efficiency and accuracy of annotating data samples for supervised machine learning algorithms using an advanced annotation pipeline. According to an embodiment, a method can comprise collecting, by a system comprising a processor, unannotated data samples for input to a machine learning model and storing the unannotated data samples in an annotation queue. The method further comprises determining, by the system, annotation priority levels for respective unannotated data samples of the unannotated data samples, selecting, by the system from amongst different annotation techniques, one or more of the different annotation techniques for annotating the respective unannotated data samples based the annotation priority levels associated with the respective unannotated data samples.
The present approach relates to determining a reference value based on image data that includes a non-occluded vascular region (such as the ascending aorta in a cardiovascular context). This reference value is compared on a pixel-by pixel basis with the CT values observed in the other vasculature regions. With this in mind, and in a cardiovascular context, the determined FFR value for each pixel is the ratio of CT value in the vascular region of interest to the reference CT value.
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
92.
METHODS AND SYSTEMS FOR IMAGING A NEEDLE FROM ULTRASOUND IMAGING DATA
Various methods and systems are provided for imaging a needle using an ultrasound imager. In one example, a method may include receiving a target path or a target area of a needle, and adjusting a steering angle of an ultrasound beam emitted from an ultrasound probe based on the target path or the target area.
A61B 8/08 - Detecting organic movements or changes, e.g. tumours, cysts, swellings
A61B 8/00 - Diagnosis using ultrasonic, sonic or infrasonic waves
G01S 7/52 - RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES - Details of systems according to groups , , of systems according to group
93.
IMAGE PROCESSING AND ROUTING USING AI ORCHESTRATION
Systems, methods, and apparatus to generate and utilize predictive workflow analytics and inferencing are disclosed and described. An example apparatus includes an algorithm orchestrator to analyze medical data and associated metadata and select an algorithm based on the analysis. The example apparatus includes a postprocessor to execute the algorithm with respect to the medical data using one or more processing elements. In the example apparatus, the one or more processing elements are to be dynamically selected and arranged in combination by the algorithm orchestrator to implement the algorithm for the medical data, the postprocessor to output a result of the algorithm for action by the algorithm orchestrator.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
94.
ADAPTIVE MEDICAL IMAGING DEVICE CONFIGURATION USING ARTIFICIAL INTELLIGENCE
Methods, apparatus, systems and articles of manufacture to provide a mutatable machine genetic structure are disclosed. An example apparatus includes memory including instructions for execution by a processor and a machine genetic structure specifying composition, performance, and health of a machine; and at least one processor. The processor is to execute the instructions to at least: evaluate the machine genetic structure with respect to an operating condition of the machine to identify a discrepancy and/or an opportunity for improvement for the machine genetic structure to satisfy the operating condition; determine a mutation of the machine genetic structure from a first sequence to a second sequence to address the discrepancy and/or opportunity for improvement to satisfy the operating condition; and set the machine genetic structure from the first sequence to the mutation of the second sequence to configure the machine for operation according to the machine genetic structure.
A method for making ultrasound transducers and ultrasound probes includes providing a piezoelectric layer having a first surface and a second surface, where the second surface is on an opposite side of the piezoelectric layer from the first surface. The method includes fabricating a plurality of conductive through vias extending from the first surface to the second surface of the piezoelectric layer, where fabricating the plurality of conductive through vias comprises cutting a plurality of trenches through the piezoelectric layer and filling each of the plurality of trenches with a conductive material. The method includes cutting the piezoelectric layer into a plurality of transducer units after fabricating the plurality of conductive through vias and cutting each of the transducer units into a plurality of transducer elements.
B06B 1/06 - Processes or apparatus for generating mechanical vibrations of infrasonic, sonic or ultrasonic frequency making use of electrical energy operating with piezoelectric effect or with electrostriction
96.
SYSTEMS AND METHODS FOR SUSTAINED BREATH DELIVERY TO NEONATES
A T-piece for ventilating a neonate includes a body having three ports, including an air supply connection port configured to connect to an air supply hose to receive gas therefrom, a mask connection port configured to connect to a neonatal ventilation mask, and a positive end-expiratory pressure (PEEP) control port. A PEEP adjustor cap is connected to the PEEP control port, the PEEP adjustor cap having a bypass hole to allow gas to exit the T-piece and configured such that when the bypass hole is closed substantially all gas received at the air supply connection port is directed to the neonate, and when the bypass hole is open at least a portion of the gas received at the air supply connection port exits through the bypass hole. The T-piece is configured such that the bypass hole can be closed to deliver a sustained breath procedure to a neonate. A sustained breath delivery timer configured to limit a duration of the sustained breath procedure.
A multi- sensor patch for simultaneous abdominal monitoring of maternal and fetal physiological data includes a multi-layer flexible substrate with a center region and a plurality of electrode regions. A conductive layer of the flexile substrate provides an electrical connection between each of the plurality of electrode regions and the center region. A plurality of electrodes are formed into the flexible substrate. At least one mechanical motion sensor is connected to the multi-layer flexible substrate. A module unit is connected to the conductive layer at the center region. The module unit includes a controller configured to receive biopotential physiological data from the plurality of electrodes and mechanical sensor data from the at least one auxiliary sensor. The controller calculates at least fetal heart rate, maternal heart rate, and uterine activity from the biopotential physiological data and from the mechanical sensor data.
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
Various methods and systems are provided for a fabric cover including a plurality of integrated electrodes for measuring an electrocardiogram signal of a patient in direct contact with at least a subset of the plurality of integrate electrodes. As one example, a fabric cover for an infant incubator or warmer includes a plurality of electrodes spaced apart from one another within a measurement area of a surface of the fabric cover adapted to have direct contact with a patient, the plurality of electrodes including a topmost electrode extending across an entire width of the measurement area, a bottommost electrode extending across the entire width of the measurement area, and a set of electrodes arranged between the topmost electrode and bottommost electrode, in a direction perpendicular to the width, within the measurement area.
The disclosed sensor assembly may be used in a patient monitoring system to monitor one or more physiological parameters of a patient. The sensor assembly may include a substrate and one or more electrodes, which may include a lattice structure to limit a contact area between the one or more electrodes and skin of the patient. The sensor assembly may include connectors or connector assemblies that facilitate connection between the one or more electrodes and a data acquisition unit. The sensor assembly may be especially useful for patients with sensitive skin, such as infants in a neonatal intensive care unit (NICU).
Systems and computer-implemented methods for facilitating automated compression of artificial neural networks using an iterative hybrid reinforcement learning approach are provided. In various embodiments, a compression architecture can receive as input an original neural network to be compressed. The architecture can perform one or more compression actions to compress the original neural network into a compressed neural network. The architecture can then generate a reward signal quantifying how well the original neural network was compressed. In (α)-proportion of compression iterations/episodes, where α ∈ [0,1], the reward signal can be computed in model-free fashion based on a compression ratio and accuracy ratio of the compressed neural network. In (1 — α) -proportion of compression iterations/episodes, the reward signal can be predicted in model-based fashion using a compression model learned/trained on the reward signals computed in model-free fashion. This hybrid model-free- and-model-based architecture can greatly reduce convergence time without sacrificing substantial accuracy.
patents
