Psychosis Relapse Prediction Leveraging Electronic Health Records Data and Natural Language Processing Enrichment Methods

Psychosis Relapse Prediction Leveraging Electronic Health Records Data and Natural Language Processing Enrichment Methods

BackgroundIdentifying patients at a high risk of psychosis relapse is crucial for early interventions. A relevant psychiatric clinical context is often recorded in clinical notes; however, the utilization of unstructured data remains limited. This study aimed to develop psychosis-relapse prediction...

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Bibliographic Details
Main Authors: Dong Yun Lee, Chungsoo Kim, Seongwon Lee, Sang Joon Son, Sun-Mi Cho, Yong Hyuk Cho, Jaegyun Lim, Rae Woong Park
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-04-01
Series:Frontiers in Psychiatry
Subjects:
natural language processing
psychotic disorder
recurrence
models
statistical
electronic health records
Online Access:https://www.frontiersin.org/articles/10.3389/fpsyt.2022.844442/full

Internet

https://www.frontiersin.org/articles/10.3389/fpsyt.2022.844442/full

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