Aetna Inc.

Qin Li

Ryan T Berns

Naiqian Zhi

Rajiv Bhan

Alex Xu

Sarah Wohlman

Alan Leggitt

Sumeet Kumar

A system and method are disclosed for detecting chronic health conditions based on data collected by a wearable device such as an activity tracker or a smart watch. Deep learning algorithms are configured to process the monitored parameter data collected by the wearable device as well as additional embedding data obtained from health records corresponding to a user account registered to the wearable device. In some examples, the input vector can also include embedding data related to social determinants data and/or demographic data. The output of the deep learning algorithms provides predictions that represent probabilities that the user of the wearable device has an underlying health condition. If any underlying health condition is detected, then the user can be notified directly, via the wearable device or an associated application or technology, or indirectly, via a primary care provider associated with the user.

Machine learning framework for detection of chronic health conditions

Growing community of inventors

Hartford, CT, United States of America

Qin Li