Abstract: A system for generating a viral alleviation program including a computing device configured to receive at least a viral biomarker relating to a user, retrieve a viral epidemiological profile, identify, using the viral epidemiological profile, a plurality of nutrition elements for the user, wherein identifying includes assigning the viral epidemiological profile to a viral infection category, calculating, according to the viral infection category, a plurality of nutrient amounts, wherein calculating a plurality of nutrient amounts includes determining an effect of the plurality of nutrient amounts on the viral epidemiological profile, and calculating the plurality of nutrient amounts as a function of the effect, identifying, as a function of the plurality of nutrient amounts, the plurality of nutrition elements, wherein the plurality of nutrition elements are intended to prevent viral infection as a function of the viral infection category, and generate, using the plurality of nutrition elements, viral allevia

Abstract: A method (and the associated system) for risk evaluation in a vascular region of interest V are provided, making it possible, based on a fluidic study and/or on a treatment algorithm using a learning method, to generate risk models MR predictively indicating the risk level NR for the occurrence of events such as: occurrence and rupture of an aneurysm, coarctation, etc., and the associated anatomical areas. The models MR are intended to serve as an assistance support for the medical decision-making of a physician.

Abstract: A system including a range of motion module, a quality of sleep module, an overall module, and a control module. The range of motion module, subsequent to performing a procedure on a patient, determines a first range of motion score of the patient based on a signal generated by a sensor. The quality of sleep module, subsequent to performing the procedure on the patient, determines a first quality of sleep score or a first pain score based on the signal generated by the sensor. The overall module determines a combined score based on (i) the first range of motion score, and (ii) the first sleep score or the first pain score. The control module (i) determines whether an outcome of the procedure is positive based on the combined score, and (ii) stores the determined outcome and the combined score in a memory.

Abstract: A method for providing a computer implemented medical diagnosis includes receiving an input from a user comprising a symptom of the user. The method also includes providing the symptom as an input to a medical model comprising a probabilistic graphical model comprising probability distributions and relationships between symptoms and diseases, and an inference engine configured to perform Bayesian inference on said probabilistic graphical model. The method also includes generating a question for the user to obtain further information concerning the user to allow a diagnosis, and outputting said question to the user. The method also includes outputting said question to the user, wherein generating a question for the user comprises ranking said questions by determining the utility of the possible questions.

Abstract: A power-optimized eco-system for tracking a user's health comprises: one or more wearable remote sensors, each wirelessly communicating only with one wearable central sensor; a portable device readily accessible to the user; and a cloud platform. Each sensor is configured to measure data indicative of one or more physiological parameters. The central sensor is configured to receive and subsequently process data measured by each remote sensor, to process data measured by the central sensor, and to generate corresponding instructions. The portable device comprises: a receiver wirelessly receiving the processed data and instructions from the central sensor; a processor running a mobile application handling the processed data and instructions; and a transmitter. The cloud platform is configured to: receive the processed data from the transmitter; analyze the received processed data; and transmit the results of the analysis to at least one of the portable device and an authorized healthcare entity.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for collecting monitoring data and predicting outcomes for communities. In some implementations, monitoring data is received, including location tracking data that indicates locations visited by individuals in a community. Community data for the community that describes characteristics of the community and a geographic region associated with the community is received. One or more predictive models are used to evaluate regions for potential for transmission of a disease based on behavior patterns of individuals in the community. The one or more predictive models can be models trained based on training data describing a plurality of different communities and behavior patterns and disease outcomes of individuals in the different communities over time.

Abstract: A web-based interface enables medical personnel to remotely monitor medical devices. A monitoring system records operational data and alarms from the medical devices in a file. However, since network connections between the medical devices and the monitoring system are intermittent, the file does not contain a contiguous stream of data for each medical device. The file pauses recording during gaps in network connectivity. The system displays current data, as well as a list of alarms. If medical personnel wish to view more detail about an earlier time or one of the alarms, the system calculates where in the file the medical device data was recorded. This calculation accounts for the discontiguous nature of the data. The system uses times the network connection is made and broken to calculate an index into the file that corresponds to the time of the user-selected alarm.

Abstract: Systems and methods are provided for providing diabetes patient treatment guidance for a patient in which a biochemical data set is obtained. The biochemical data set comprises test results from a single blood draw of the patient including at least three measurements selected from the set: a high-sensitivity c-reactive protein test, an adiponectin level test, an intact proinsulin level test, an insulin level test, a C-peptide test, a HbA1c test, and an eGFR level test. A demographic data set for the patient is also obtained that comprises the patient's gender and diabetes stage. The biochemical data set and demographic data set is run against one or more rules to determine a first patient therapy pattern. Then, a report is prepared based on an identity of the first therapy patient pattern. The report sets priorities among intervention classes for the patient based on the identity of the first patient pattern.

Abstract: An operation checking unit for a dialysis apparatus (such as a hemodialysis or peritoneal dialysis machine) is disclosed which comprises an identification unit which is configured to detect a user identity of a user. The operation checking unit also comprises a sensor unit which is configured to detect an operating action of the identified user as an ACTUAL-operation data set, and a processing unit which is configured to compare the detected ACTUAL-operation data set with a DESIRED-operation data set stored in a memory in order to generate a user-specific message in the event of a discrepancy.

Abstract: Various embodiments for configuring a medical database by a processor in communication with at least one storage device in a computing environment are provided. Medical data are assigned to a patient. A plurality of data types is organized for the medical data. Portions of each of the plurality of data types are designated as public and private data. A plurality of access levels is organized for the medical data. Each of the plurality of data types includes the plurality of access levels. A first access level of the plurality of access levels corresponds to the patient. The medical data is classified according to the plurality of data types, for each of the plurality of data types, according to the plurality of access levels, and according to one of the public and the private data. The medical data is encrypted in a hierarchical structure corresponding to each of the plurality of access levels.

Abstract: Systems and methods include one or more entities including a sensor configured to provide data in at least a first protocol or standard from a first manufacturer and a second protocol or standard from a second manufacturer; and an electronic health record database configured to translate between the protocols and save the data in an intermediate format.

Abstract: A machine learning system for training a data model to predict data states in medical orders is described. The machine learning system is configured to train a data model to predict whether a medical order requires prior authorization (“PA”) for medical orders within a medical order data set so that related systems may process incoming medical orders with PA determinations predicted by the data model. The machine learning system includes a first data warehouse system. The first prescription processing system generates a data model of historical orders and payer responses, apply a predictive machine learning model to the data model to generate a trained predictor of whether a medical order requires PA, associated with order data, apply the trained predictor to a plurality of production orders to determine PA for each of the plurality of production orders, and process the plurality of production orders with each associated PA determination.

Abstract: Embodiments describe an approach to monitoring user health data. Determining if the user is having an emergency based on the user health data. Responsive to determining the user is having an emergency the user's location. Identifying one or more available parking spaces based on the user's location, and outputting locations of one or more available parking spaces to the user.

Abstract: A system and method for post-case analysis of cardiopulmonary resuscitation (CPR) performance trends is described. Such a system includes a processor configured to communicatively couple to a CPR metrics devices and to an output device and a memory including processor-executable instructions configured to cause the processor to receive, from the CPR metrics devices, treatment data including CPR performance data collected by the CPR metrics devices during medical treatment of one or more individuals, determine, from the CPR performance data, CPR performance metrics including a motion-based chest release parameter and at least one of chest compression depth and chest compression rate, and control the output device to concurrently display time trends of the CPR performance metrics, wherein the time trends indicate values of the CPR performance metrics over two or more equal time intervals during the medical treatment of the one or more individuals.

Abstract: Systems, methods and computer-readable media are provided for facilitating clinical decision support and managing patient population health by health-related entities including caregivers, health care administrators, insurance providers, and patients.

Abstract: A method for determining a disease state transition path includes receiving a patient data having functional data and/or structural data related to a patient. Based on the patient data, a first disease state of a plurality of non-overlapping disease states each associated with a predetermined range of functional and/or structural degeneration values may be identified. A second, non-adjacent disease state of the plurality of disease states may be identified based on the patient data. A most probable path between the first disease state and the second disease state may be determined using a two dimensional continuous-time hidden Markov model.

Abstract: Mechanisms are provided for performing entity differentiation. A cognitive medical system ingests a corpus of medical content having references to medical entities, and performs entity recognition on the medical content to identify the medical entities. Responsive to the cognitive medical system identifying a medical entity having a plurality of annotations for a same medical entity attribute, an entity differentiation component executes an ordered set of entity differentiation algorithms, corresponding to the medical entity, for differentiating medical entity attribute values. The entity differentiation component runs the ordered set of entity differentiation algorithms, in order, on the plurality of annotations for the attribute to generate a ranked list of medical entity attribute values corresponding to the annotations in the plurality of annotations. The cognitive medical system performs a cognitive operation on the medical entity based on the ranked list of medical entity attribute values.

Abstract: A system is provided to provide triage recommendations for animals. The system accesses a syndrome mapping of syndromes to complaints, each syndrome having a triage category. The system accesses a complaint mapping of complaints to symptoms. Each symptom for a complaint has a weight. The system receives indications of a current complaint and current symptoms of an animal. Each current symptom has a score. The system identifies the triage category based on a syndrome to which the current complaint and the current symptoms apply, factoring in the weights and the scores. The system provides a recommendation for the animal based on the identified triage category.

Abstract: An electronic image that includes information related to a pharmacy prescription of a user of a first account (e.g., a store account) is received from a client device. The pharmacy prescription information is electronically extracted from the electronic image, and a second account (e.g., a pharmacy account) is identified based thereon. If the user of the first account is different from the user of the second account and if the user of the second account has approved the user of the first account, the user of the first account is granted access to a subset of the information in the pharmacy account.

Abstract: An electronic image that includes information related to a pharmacy prescription of a user of a first account (e.g., a store account) is received from a client device. The pharmacy prescription information is electronically extracted from the electronic image, and a second account (e.g., a pharmacy account) is identified based thereon. Additional authentication information is received from the client device (sometimes in response to a prompt for additional information based on information contained in the first or second accounts), and the first and second accounts are linked if the additional authentication information is consistent with the user.