Support vector machine deep mining of electronic medical records to predict the prognosis of severe acute myocardial infarction.

Zhou, Xingyu; Li, Xianying; Zhang, Zijun; Han, Qinrong; Deng, Huijiao; Jiang, Yi; Tang, Chunxiao; Yang, Lin

Zhou, Xingyu; Li, Xianying; Zhang, Zijun; Han, Qinrong; Deng, Huijiao; Jiang, Yi; Tang, Chunxiao; Yang, Lin.

Affiliation

Zhou X; Zhuhai Campus of Zunyi Medical University, Zhuhai, China.
Li X; Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (CAS), Shenzhen, China.
Zhang Z; Zhuhai Campus of Zunyi Medical University, Zhuhai, China.
Han Q; Zhuhai Campus of Zunyi Medical University, Zhuhai, China.
Deng H; Zhuhai Campus of Zunyi Medical University, Zhuhai, China.
Jiang Y; Zhuhai Campus of Zunyi Medical University, Zhuhai, China.
Tang C; Zhuhai Campus of Zunyi Medical University, Zhuhai, China.
Yang L; Zhuhai Campus of Zunyi Medical University, Zhuhai, China.

Front Physiol ; 13: 991990, 2022.

Article in En | MEDLINE | ID: mdl-36246101

Key words

ICU; cardiology; electronic medical records; machine learning; support vector machine

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Full text: 1 Collection: 01-internacional Health context: 1_ASSA2030 Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Front Physiol Year: 2022 Document type: Article

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