Health Outcomes Sciences, LLC

Washington University

Gabriel Enrique Soto

John Albert Spertus

Scott J Hultgren

Fredrik Almqvist

Physiological sensors may be utilized to obtain physiological data for a user. The sensor data may be utilized in predicting a user's outcome to a medical intervention using one or more models. The models may be automatically executed in response to receiving certain types and/or amount of data, such as data received from one or more physiological remote sensors, such as Internet of Things sensors. The sensors may include heart rate sensors, arterial pressure sensors, glucose sensors, temperature sensors, weight sensors, blood oxygen sensors, urine sensors, saliva sensors, skin conduction sensors, muscle sensors, brain signal sensors, and/or other sensors. A sensor may communicate over the 2360-2400 MHz and/or the 30-37.5 MHz radio frequency (RF) band. The data may be received from a networked data store. Execution of the models may identify health issues in substantially real time, and the operation of one or more medical devices may be modified and/or a communication may be generated.

Systems and methods for utilizing wireless physiological sensors

A method for providing decision support includes using a programmed computer to input a regression model specification, and to repeat the input a plurality of times to obtain and store a plurality of regression model specifications. The method further includes using the programmed computer to analyze selected regression model specifications to determine at least one of common variables and functions of common variables, to thereby determine a reduced-redundancy request for input of variables, when a plurality of the stored regression model specifications are selected for use.

Methods and systems for utilizing prediction models in healthcare

A statistical processing system includes a server operably configured with program instructions implementing a plurality of statistical models to at least one of (a) predict a health outcome based on questionnaire responses, (b) assist a patient's choice of therapeutic modality based on questionnaire responses, and (c) assess a health risk or status based on questionnaire responses. Also provided is a research agency communicating with the server and contracted to provide the statistical models using a visual interface communicated by the server. The server is configured to analyze requests received from users relating to a plurality of said statistical models to reduce redundancy in requests for patient data.

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Chesterfield, MO, United States of America

Gabriel Enrique Soto