Aetna Inc.

Ryan Berns

Sarah Wohlman

Alex Xu

Naiqian Zhi

Rajiv Bhan

A system and method are disclosed for predicting short term health outcomes based on data collected by a wearable device such as an activity tracker or a smart watch. Artificial Intelligence (AI) algorithms are configured to process an input vector that includes monitored parameter data collected by the wearable device as well as embedding data obtained from health records corresponding to a user account registered to the wearable device. In particular, a framework is defined that includes a random forest model configured to classify a user based on the monitored parameter data and embedding data. Based on a positive health outcome classification, a minimum value is assigned to a health index value for the user or, based on a negative health outcome classification, a gradient boosting machine is configured to generate the health index value. Various operations can be performed based on the assigned health index value for the user.

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Hartford, CT, United States of America

Ryan Berns