A fitting machine learning prediction model for short-term mortality following percutaneous catheterization intervention: a nationwide population-based study.

Journal: Annals of translational medicine
Published Date: Dec 1, 2019

Abstract

BACKGROUND: A suitable multivariate predictor for predicting mortality following percutaneous coronary intervention (PCI) remains undetermined. We used a nationwide database to construct mortality prediction models to find the appropriate model.

Authors

  • Meng-Hsuen Hsieh
    Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, USA.
  • Shih-Yi Lin
    Graduate Institute of Biomedical Sciences, China Medical University, Taichung.
  • Cheng-Li Lin
    Management Office for Health Data, China Medical University Hospital, Taichung.
  • Meng-Ju Hsieh
    Department of Medicine, Poznan University of Medical Sciences, Poznan, Poland.
  • Wu-Huei Hsu
    Graduate Institute of Biomedical Sciences, China Medical University, Taichung.
  • Shu-Woei Ju
    Graduate Institute of Biomedical Sciences, China Medical University, Taichung.
  • Cheng-Chieh Lin
    Graduate Institute of Biomedical Sciences, China Medical University, Taichung.
  • Chung Y Hsu
    Graduate Institute of Biomedical Sciences, China Medical University, Taichung.
  • Chia-Hung Kao
    Graduate Institute of Biomedical Sciences, China Medical University, Taichung.

Keywords

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