Unitedhealth Group Incorporated

Herk Anthony Confer

Jared Dustin Martin

Daniel Joseph Mulcahy

Rony Krell

Tanzeem Choudhury

Brendon Sean Hale

Cecilia M Livesey

Laura Kirschbaum Kochevar

Mohsen Afrasiabi

A method for determining a treatment recommendation using a multi-armed bandit (MAB) model can include receiving first patient information, determining, using the MAB model, the treatment recommendation based on the first patient information, wherein the MAB model is trained based on a MAB treatment recommendation determined by the MAB model using second patient information and a clinical treatment recommendation determined according to clinical guidelines based on the second patient information, and providing the treatment recommendation.

Systems and methods for training multi-armed bandit models

There is a need to dynamically determine one or more levels of difficulty for a computer program associated with one or more levels of difficulty for a computer program associated with one or more dynamic difficulty tasks. In one example, embodiments comprise, during a user interaction session with a computer program, receiving a physiological evaluation data object. One or more physiological difficulty levels may be determined based at least in part on the physiological evaluation data object. One or more program control parameter values for one or more program control parameters may be determined based at least in part on the one or more physiological difficulty levels. User interface data for the computer program may be generated to enable rendering of an in-program experience of the computer program as adjusted by the one or more program control parameter values.

Methods and apparatuses for dynamic determination of computer program difficulty

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San Francisco, CA, United States of America

Herk Anthony Confer