Proxy model using mobile device data to provide health indicators

    公开(公告)号:US12002587B1

    公开(公告)日:2024-06-04

    申请号:US15880043

    申请日:2018-01-25

    申请人: BLUEOWL, LLC

    IPC分类号: G16H50/30 G06N3/08 G16H50/50

    CPC分类号: G16H50/30 G06N3/08 G16H50/50

    摘要: Systems and methods are provided for determining a health indicator, such as a life expectancy, of a target person using a proxy model comprising an artificial neural network, in lieu of more complex, costly, and/or invasive health assessment processes. The artificial neural network may be constructed from labeled training data comprising a plurality of activity data training sets, each set including personal activity metrics associated with activities performed by a respective training person as derived from sensor data obtained via one or more mobile electronic devices (e.g., a smartphone or a wearable device) of the respective training person. The trained artificial neural network may then obtain and process an activity data set associated with the target person to determine a health indicator of the target person.

    PREDICTION METHOD USING STATIC AND DYNAMIC DATA

    公开(公告)号:US20240161930A1

    公开(公告)日:2024-05-16

    申请号:US18231110

    申请日:2023-08-07

    申请人: VUNO Inc.

    IPC分类号: G16H50/30 G16H50/50 G16H50/70

    CPC分类号: G16H50/30 G16H50/50 G16H50/70

    摘要: Disclosed is a method for generating a prediction result by using static data and dynamic data according to an exemplary embodiment of the present disclosure. Specifically, according to the present disclosure, a computing device generates an integrated feature vector from static data and dynamic data of input data by using an artificial neural network model. The computing device generates a dynamic feature vector from the dynamic data of the input data by using the artificial neural network model. The computing device generates a final prediction result of the artificial neural network model based on the integrated feature vector and the dynamic feature vector.