- 专利标题: PROCESSING EVENT DATA BASED ON MACHINE LEARNING
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申请号: US18088074申请日: 2022-12-23
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公开(公告)号: US20240211800A1公开(公告)日: 2024-06-27
- 发明人: Eileen Kasda , Christine Robson , Asa Adadey , David Gillen , Mario Koym-Garza
- 申请人: The Johns Hopkins University
- 申请人地址: US MD Baltimore
- 专利权人: The Johns Hopkins University
- 当前专利权人: The Johns Hopkins University
- 当前专利权人地址: US MD Baltimore
- 主分类号: G06N20/00
- IPC分类号: G06N20/00 ; G06F18/23213
摘要:
A computer-implemented method includes receiving, by a data processing system, event data representing a medical safety event. The method includes processing the event data, including: parsing, the event data to identify a structure of the event data; and identifying one or more fields from the structure of the event data. The method includes inputting, to a machine learning engine, contents of the one or more fields. The method includes generating, by the machine learning engine and from contents of the one or more fields, one or more feature vectors. The method includes accessing a plurality of indicator candidates. The method includes determining, by the machine learning engine and based on the one or more feature vectors, one or more indicators from the indicator candidates. The method includes tagging the event data with the one or more indicators. The method includes storing the tagged event data in a hardware storage device.
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