Optum, Inc.

Mary Duncan

Daniel J Mulcahy

Christina Winans Burke

Zhongjian Liu

Machine-learning based recommendation engines are configured to execute machine-learning models to generate recommendations as output for a user based at least in part on functional data received at the recommendation engine. The recommendation engine is further configured to automatically determine the relative importance of one or more functional data entries in generating the recommendation. Moreover, the recommendation engine executes additional machine-learning models, including a machine-learning model trained to avoid negative outcomes, and an opportunity-based machine-learning model to identify alternative recommendation options based on alternative training logic.

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Washington, DC, United States of America

Mary Duncan