External validation of a machine learning model to predict hemodynamic instability in intensive care unit.

Journal: Critical care (London, England)
Published Date: Jul 14, 2022

Abstract

BACKGROUND: Early prediction model of hemodynamic instability has the potential to improve the critical care, whereas limited external validation on the generalizability. We aimed to independently validate the Hemodynamic Stability Index (HSI), a multi-parameter machine learning model, in predicting hemodynamic instability in Asian patients.

Authors

  • Chiang Dung-Hung
    Department of Critical Care Medicine, Taipei Veteran General Hospital, No. 201, Section 2, Shih-Pai Road, Taipei, 11217, Taiwan.
  • Tian Cong
    Philips Research China, Shanghai, 200072, China.
  • Jiang Zeyu
    Philips Research China, Shanghai, 200072, China.
  • Ou-Yang Yu-Shan
    Department of Critical Care Medicine, Taipei Veteran General Hospital, No. 201, Section 2, Shih-Pai Road, Taipei, 11217, Taiwan.
  • Lin Yung-Yan
    Department of Critical Care Medicine, Taipei Veteran General Hospital, No. 201, Section 2, Shih-Pai Road, Taipei, 11217, Taiwan. yylin@vghtpe.gov.tw.

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