Evaluation of machine learning methods to stroke outcome prediction using a nationwide disease registry.

Journal: Computer methods and programs in biomedicine
PMID: 32044620

Abstract

INTRODUCTION: Being able to predict functional outcomes after a stroke is highly desirable for clinicians. This allows clinicians to set reasonable goals with patients and relatives, and to reach shared after-care decisions for recovery or rehabilitation. The aim of this study was to apply various machine learning (ML) methods for 90-day stroke outcome predictions, using a nationwide disease registry.

Authors

  • Ching-Heng Lin
    Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan.
  • Kai-Cheng Hsu
    Bioinformatics Section, National Institute of Neurological Disorder and Stroke, National Institutes of Health, Bethesda, MD, United States; Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan.
  • Kory R Johnson
    Bioinformatics Section, National Institute of Neurological Disorder and Stroke, National Institutes of Health, Bethesda, MD, United States.
  • Yang C Fann
    Bioinformatics Section, National Institute of Neurological Disorder and Stroke, National Institutes of Health, Bethesda, MD, United States. Electronic address: fann@ninds.nih.gov.
  • Chon-Haw Tsai
    Division of Nephrology, China Medical University Hospital, Taichung, Taiwan.
  • Yu Sun
    Department of Neurology, China-Japan Friendship Hospital, Beijing, China.
  • Li-Ming Lien
    Department of Neurology, Shin Kong Wu-Ho-Su Memorial Hospital, Taipei, Taiwan; Department of Neurology, College of Medicine, Taipei Medical University, Taipei, Taiwan.
  • Wei-Lun Chang
    Department of Neurology, Show Chwan Memorial Hospital, Changhua County, Taiwan.
  • Po-Lin Chen
    Division of Cardiovascular Surgery, Department of Surgery, Taipei Veterans General Hospital, Taipei, Taiwan; Institute of Clinical Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan.
  • Cheng-Li Lin
    Management Office for Health Data, China Medical University Hospital, Taichung.
  • Chung Y Hsu
    Graduate Institute of Biomedical Sciences, China Medical University, Taichung.

Keywords

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