Real-time AI prediction for major adverse cardiac events in emergency department patients with chest pain.

Journal: Scandinavian journal of trauma, resuscitation and emergency medicine
PMID: 32917261

Abstract

BACKGROUND: A big-data-driven and artificial intelligence (AI) with machine learning (ML) approach has never been integrated with the hospital information system (HIS) for predicting major adverse cardiac events (MACE) in patients with chest pain in the emergency department (ED). Therefore, we conducted the present study to clarify it.

Authors

  • Pei-I Zhang
    Department of Emergency Medicine, Chi Mei Medical Center, Liouying, Tainan, Taiwan.
  • Chien-Chin Hsu
    Department of Emergency Medicine, Chi Mei Medical Center, 901 Zhonghua Road, Yongkang District, Tainan City, 710, Taiwan.
  • Yuan Kao
    Department of Emergency Medicine, Chi Mei Medical Center, 901 Zhonghua Road, Yongkang District, Tainan City, 710, Taiwan.
  • Chia-Jung Chen
    Information Systems, Chi Mei Medical Center, Tainan, Taiwan.
  • Ya-Wei Kuo
    Center for Quality Management, Chi Mei Medical Center, Tainan, Taiwan.
  • Shu-Lien Hsu
    Department of Nursing, Chi Mei Medical Center, Tainan, Taiwan.
  • Tzu-Lan Liu
    Information Systems, Chi Mei Medical Center, Tainan, Taiwan.
  • Hung-Jung Lin
    Department of Emergency Medicine, Chi Mei Medical Center, 901 Zhonghua Road, Yongkang District, Tainan City, 710, Taiwan.
  • Jhi-Joung Wang
    Department of Medical Research, Chi Mei Medical Center, Tainan, Taiwan.
  • Chung-Feng Liu
    Department of Medical Research, Chi Mei Medical Center, 901 Zhonghua Road, Yongkang District, Tainan City, 710, Taiwan.
  • Chien-Cheng Huang
    Department of Emergency Medicine, Chi Mei Medical Center, Tainan, Taiwan.

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