Short- and long-term mortality prediction after an acute ST-elevation myocardial infarction (STEMI) in Asians: A machine learning approach.

Journal: PloS one
PMID: 34339432

Abstract

BACKGROUND: Conventional risk score for predicting short and long-term mortality following an ST-segment elevation myocardial infarction (STEMI) is often not population specific.

Authors

  • Firdaus Aziz
    Bioinformatics Division, Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia.
  • Sorayya Malek
    Bioinformatics Division, Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia.
  • Khairul Shafiq Ibrahim
    Cardiology Department, Faculty of Medicine, Universiti Teknologi MARA (UiTM), Shah Alam, Malaysia.
  • Raja Ezman Raja Shariff
    Cardiology Department, Faculty of Medicine, Universiti Teknologi MARA (UiTM), Shah Alam, Malaysia.
  • Wan Azman Wan Ahmad
    National Heart Association of Malaysia, Heart House, Kuala Lumpur, Malaysia.
  • Rosli Mohd Ali
    Cardiac Vascular Sentral Kuala Lumpur, Kuala Lumpur, Malaysia.
  • Kien Ting Liu
    National Heart Association of Malaysia, Heart House, Kuala Lumpur, Malaysia.
  • Gunavathy Selvaraj
    National Heart Association of Malaysia, Heart House, Kuala Lumpur, Malaysia.
  • Sazzli Kasim
    Cardiology Department, Faculty of Medicine, Universiti Teknologi MARA (UiTM), Shah Alam, Malaysia.

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