Machine Learning Models for Survival and Neurological Outcome Prediction of Out-of-Hospital Cardiac Arrest Patients.

Journal: BioMed research international
PMID: 34589553

Abstract

BACKGROUND: Out-of-hospital cardiac arrest (OHCA) is a major health problem worldwide, and neurologic injury remains the leading cause of morbidity and mortality among survivors of OHCA. The purpose of this study was to investigate whether a machine learning algorithm could detect complex dependencies between clinical variables in emergency departments in OHCA survivors and perform reliable predictions of favorable neurologic outcomes.

Authors

  • Chi-Yung Cheng
    Department of Emergency Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan.
  • I-Min Chiu
    Department of Emergency Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung, Taiwan.
  • Wun-Huei Zeng
    Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan.
  • Chih-Min Tsai
    Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan.
  • Chun-Hung Richard Lin
    Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan.

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