Abstract: Methods, systems, and computer-readable media for multi-domain, multi-modal data segmentation, and automatically generating and refining hypotheses. The method receives data from a plurality of data sources; synthesizing the receive data; identifying trigger event data based on the synthesized data; generating an episode based on a segmentation of the synthesized data and trigger event data; and identifying at least one set of observational features associated with the episode based on the synthesized data and a relevancy metric. The method also includes iteratively generating a hypothesis based on the observational features using machine learning, predicting an outcome based on the hypothesis using machine learning, generating an outcome measure, and validating the hypothesis based on the outcome measure.

Abstract: Methods and systems for mobile automation control of disease spread are disclosed. A computer-implemented method includes: determining, by a computing device, a health status of a person; determining, by the computing device, that the person is sick based on the health status; determining, by the computing device, facial and body movements of the person determined to be sick; determining, by the computing device, that the person determined to be sick performed a germ-transmitting activity based on the facial and body movements; and deploying, by the computing device, a cleaning robot to clean based on the determining that the person determined to be sick performed the germ-transmitting activity.

Abstract: A system and method for extracting data from an electronic health record to provide provider and patient data similarity scoring includes: encoding a problem list for a plurality of patients with concepts from a common electronic health record ontology. In one aspect, the patients have electronic health records maintained by a plurality of providers. The system and method then may parse the concepts into a plurality of clusters or categories and determining, for each of the providers, a total number of patients that have at least one problem in a cluster or category or determining, for each patient, which of the plurality of clusters or categories correspond to at least one concept encoded in the patient's problem list. The system and method then may calculate for each pair of providers or patients, a distance between the providers or patients.

Abstract: A method and system for managing health care patient record data including identifying and conveying recordation and temporal inconsistencies in health care patient data pertaining to chronic illnesses. An embodiment of the present invention includes identifying a first health care encounter date on which a chronic illness is recorded in a patient's digital health care data and determining if the chronic illness was recorded in the patient's digital health care data for each subsequent health care encounter. Some embodiments also identify the stage of the chronic illness at each encounter to determine if and how the condition of the chronic illness has changed. Some embodiments generate alerts to inform users when a preexisting chronic illness is not subsequently identified and/or if the subsequent diagnosis of the chronic illness indicates that the condition of the chronic illness has changed by some predetermined amount.

Abstract: A method, related system and apparatus are disclosed. The method is implemented by an operative set of processor executable instructions configured for execution by a processor. The method includes the acts of: determining if a monitoring client is connected to a base through a physical connection; establishing a first communications link between the monitoring client and the base through the physical connection; updating, if necessary, the interface program on the monitoring client and the base through the first communications link; establishing a second communications link between the monitoring client and the base using the first communications link; and communicating data from the base to the monitoring client using the second communications link.

Abstract: A system for determining a plurality of biological outcomes using a plurality of dimensions of biological extraction user data and artificial intelligence, the system including a computing device configured to receive, a plurality of dimensions of biological extraction data, generate, a first machine learning process comprising a plurality of biosektch measurements wherein the first machine learning process is trained as a function of training data to output a dimensional history of a user as a function of biological extraction data, output as a function of the plurality of dimensions of biological extraction data and the first machine learning process, the dimensional history of the user; and determine, using a second machine learning process and the dimensional history of the user, at least a biological outcome associated with the user.

Abstract: The disclosure provides a disease classification method and a disease classification device. The disease classification method includes: inputting samples into a first stage model and obtaining a first stage determination result; inputting first samples determined positive by the first stage model into a second stage high specificity model to obtain second samples determined to be positive and third samples determined to be negative and rule in the second samples; inputting fourth samples determined negative by the first stage model into a second stage high sensitivity model to obtain fifth samples determined to be positive and sixth samples determined to be negative and rule out the sixth samples; obtaining a second stage determination result of the second and sixth samples; and inputting the third and fifth samples not ruled in or ruled out into a third stage model and obtaining a third stage determination result of the third and fifth samples.

Abstract: A system is for infectious disease notification. The system includes at least one processor, configured to use a machine learning monitoring algorithm, trained on a large number of EMR datasets of patients, to calculate a probability for an infectious disease from a provided EMR dataset and compare the probability of the provided EMR dataset calculated with a known value. In training of the monitoring algorithm, the value represents whether there was an onset of an infectious disease or not and the monitoring algorithm is designed to adjust parameters of the monitoring algorithm. And in evaluating a notification, the value is a threshold value and the system is designed to output a notification upon the probability being greater than the threshold value.

Abstract: The present disclosure provides a method and system for scheduling vaccines in a smart city based on the Internet of Things (IoT), which is executed by a vaccine management platform. The method includes obtaining a service scope corresponding to each vaccination point in a preset area, obtaining information related to vaccine service within the service scope, the information related to the vaccine service including vaccination information, information of target persons to be vaccinated, and a time type of each preset time point, determining a prediction result based on the information related to the vaccine service within the service scope, the prediction result including a number of possible to-be-vaccinated persons at the each vaccination point at the each preset time point, and determining an allocation scheme based on the prediction result.

Abstract: The present invention, in some embodiments thereof, relates to a pharmaceutical dispensing system with dynamic and automatic pharmaceutical dispensing regimes and methods thereof.

Abstract: Monitoring devices monitor physiological parameters of a patient undergoing surgery. The physiological parameters describe a physiological condition of the patient. A processor matches the physiological parameters to stored surgical data associated with adverse surgical events associated with surgical procedures matching the surgery. The processor determines a predicted time at which the physiological condition of the patient will meet a threshold physiological condition associated with the adverse surgical event based on a rate of change of the physiological parameters. Responsive to determining the predicted time, the processor transmits a first alert to robotic surgical controls to adjust the surgery prior to the predicted time. The processor determines that the physiological condition of the patient has met the threshold physiological condition. The processor transmits a second alert to the robotic surgical controls to terminate the surgery.

Abstract: There is provided a method comprising: mapping patient-specific medications (mapped to active ingredients) and patient-specific parameters of a patient to a mapping data-structure that maps between medications, predicted medical outcomes, and patient parameters, each relationship-mapping includes one medication (active ingredient), one predicted medical outcome, one patient parameter, one risk score, a predicted medical outcome(s) denoting a medication induced event of a corresponding mapped medication, the patient parameter(s) including: a medication influencing factor (for an active ingredient, selected from primary parameters affecting the corresponding mapped medication: blood level, absorption, distribution, metabolism, elimination) directly affecting the corresponding mapped medication which affects the medication induced event, and/or an event influencing factor directly affecting the medication induced event, and computing an aggregated risk score for each respective predicted medical outcome by aggre

Abstract: Medical devices and related patient management systems and methods are provided. An exemplary system includes a medical device to obtain measurement values for a physiological condition in a body of a patient and a computing device to identify a plurality of event patterns within a plurality of monitoring periods based on the measurement values, prioritize the plurality of event patterns based on one or more prioritization criteria, filter the prioritized list of event patterns based on one or more filtering criteria, and generate a snapshot graphical user interface display. The snapshot graphical user interface display includes a graph overlay region having a graphical representation of the measurement values with respect to a time of day and an event detection region below the graph overlay region, where the event detection region includes pattern guidance displays for event patterns of the filtered prioritized list ordered according to the prioritization.

Abstract: A medical scan assisted review system is operable to receive, via a network, a medical scan for review. Abnormality data is generated by identifying a plurality of abnormalities in the medical scan by utilizing a computer vision model that is trained on a plurality of training medical scans. The abnormality data includes location data and classification data for each of the plurality of abnormalities. Text describing each of the plurality of abnormalities is generated based on the abnormality data. The abnormality data and the text is transmitted to a client device. A display device associated with the client device displays the abnormality data in conjunction with the medical scan via an interactive interface, and the display device further displays the text via the interactive interface.

Abstract: An embodiment of the present invention provides a method of creating a classifier indicative of a presence of a medical condition in a subject, comprising receiving chromatogram data indicative of a profile of volatile organic compounds in a sample from each of a first plurality of subjects having the medical condition and a second plurality of subjects without the medical condition, selecting one of the chromatogram data as reference chromatogram data, aligning the remaining chromatogram data in relation to the reference chromatogram data, extracting one or more features from the chromatogram data using a Mexican hat wavelet transform of one or more scales, selecting one or more features of the chromatogram data indicative of the medical condition, and constructing a classifier for determining a boundary between chromatogram data indicative of the medical condition and chromatogram data indicative of an absence of the medical condition.

Abstract: A portable medical triage kit and interactive application that leads a user through a medically acceptable triage protocol for treating medical emergencies. The interactive application leads the user to treat major life threats of all nearby victims before treating minor threats of anyone.

Abstract: Medical devices and related patient management systems and methods are provided. A method of presenting information pertaining to operation of a medical device involves obtaining historical glucose measurement data for a patient from a database, identifying, based on the historical glucose measurement data, a first set of event patterns within respective ones of a plurality of monitoring periods, obtaining an adjusted set of glucose measurement data determined based on the historical glucose measurement data and an uncertainty metric associated with the historical glucose measurement data, identifying, based on the adjusted set of glucose measurement data, one or more event patterns within respective ones of the plurality of monitoring periods, and generating a graphical user interface display comprising an event detection region based at least in part on the first plurality and the one or more sets of event patterns.

Abstract: Inference of appropriate anatomical region from inconsistent descriptions in order to provide fast and accurate prefetching is provided. In various embodiments, an anatomical region of a first medical imaging study is determined. A first plurality of keywords is determined corresponding to the anatomical region of the first medical imaging study. A plurality of studies is accessed having a patient in common with the first medical imaging study. A second plurality of keywords is extracted from the plurality of studies. Those of the plurality of studies having extracted keywords in common with the first plurality of keywords are selected. The selected studies are pre-fetched for display to a user.

Abstract: A data collection device is configured to capture images of a dosage indicator of a medicament delivery device and, if an injection is administered without prior confirmation of a dosage amount, to prompt the user to set a value for the delivered medicament dosage amount for storing in a dosage log. For example, the determination may be based on specific confirmation from the user or detecting a zero dosage amount in captured images. A suggested dosage amount may be displayed to the user, for example a highest or more recently programmed dosage amount prior to the injection or based on one or more previously confirmed dosage amounts. The data collection device may use one or more of optical character recognition, optical pattern recognition and determination of direction of rotation of a dosage adjustment component to determine whether an injection is being, or has been, administered and/or a suggested dosage amount.

Abstract: Disclosed herein are systems and methods for immunity data creation and immunity monitoring (e.g., management, maintenance, etc.). A user may upload immunity and redaction data. A community of other users may verify the uploaded data. A venue may comprise a target immunity level and an actual immunity level. Combining the verified uploaded data with the actual immunity level may yield a new actual immunity level. The user may be allowed to enter the venue if the new actual immunity level is at or above the target immunity level.