Invention Grant
- Patent Title: Passive data collection and use of machine-learning models for event prediction
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Application No.: US17295248Application Date: 2019-12-05
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Publication No.: US12057232B2Publication Date: 2024-08-06
- Inventor: Gari Clifford , Ayse Cakmak , Amit Shah , Erik Reinertsen
- Applicant: EMORY UNIVERSITY , GEORGIA TECH RESEARCH CORPORATION
- Applicant Address: US GA Atlanta
- Assignee: Emory University,Georgia Tech Research Foundation
- Current Assignee: Emory University,Georgia Tech Research Foundation
- Current Assignee Address: US GA Atlanta; US GA Atlanta
- Agency: Emory Patent Group
- International Application: PCT/US2019/064630 2019.12.05
- International Announcement: WO2020/118022A 2020.06.11
- Date entered country: 2021-05-19
- Main IPC: G16H50/30
- IPC: G16H50/30 ; G06F18/2431 ; G16H10/60 ; G16H40/67 ; G16H50/20 ; G16H50/70

Abstract:
Methods and systems for monitoring of sensor data for processing by machine-learning models to generate event predictions to estimate a risk a medical event are provided. An electronic device or wearable smart device may monitor the output of various sensors to collect data related to a person's activity level, location changes, and communications and may use this information as input to a personalized trained machine-learning model to predict a likelihood of an event.
Public/Granted literature
- US20210398683A1 PASSIVE DATA COLLECTION AND USE OF MACHINE-LEARNING MODELS FOR EVENT PREDICTION Public/Granted day:2021-12-23
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