Evidential MACE prediction of acute coronary syndrome using electronic health records.

Journal: BMC medical informatics and decision making
PMID: 30961585

Abstract

BACKGROUND: Major adverse cardiac event (MACE) prediction plays a key role in providing efficient and effective treatment strategies for patients with acute coronary syndrome (ACS) during their hospitalizations. Existing prediction models have limitations to cope with imprecise and ambiguous clinical information such that clinicians cannot reach to reliable MACE prediction results for individuals.

Authors

  • Danqing Hu
    College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.
  • Wei Dong
    Department of Cardiology, Chinese PLA General Hospital, Beijing, China.
  • Xudong Lu
    The College of Biomedical Engineering and Instrument Science, Zhejiang University, 310027 Hangzhou, Zhejiang, China.
  • Huilong Duan
    The College of Biomedical Engineering and Instrument Science, Zhejiang University, 310027 Hangzhou, Zhejiang, China.
  • Kunlun He
    Beijing Key Laboratory of Precision Medicine for Chronic Heart Failure, Chinese PLA General Hospital, Beijing, China.
  • Zhengxing Huang
    College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.

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