Massachusetts Institute of Technology

Anna Nichole Honko

Albert Joseph Swiston

Tejash Mukesh Patel

Jack Gerald Fleischman

William Donald Pratt

Lauren Milechin

Systems and methods are disclosed herein for predicting whether a patient has been exposed to an agent. Physiological data is recorded from the patient during a first time interval, and one or more features are extracted from the physiological data. A plurality of classifiers is identified, wherein each classifier is trained using training data for a respective specific post-exposure time interval. For each classifier and based on a respective subset of the one or more features, a patient state classification that indicates an initial prediction of whether the patient has been exposed to the agent is determined. An indication of a prediction that the patient has been exposed to the agent is provided when a number of patient state classifications indicating a positive initial prediction that the patient has been exposed to the agent exceeds a first threshold.

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Frederick, MD, United States of America

Anna Nichole Honko