Machine learning-based analyses of contributing factors for the development of hypertension: a comparative study.

Journal: Clinical and experimental hypertension (New York, N.Y. : 1993)
PMID: 39773295

Abstract

OBJECTIVES: Sufficient attention has not been given to machine learning (ML) models using longitudinal data for investigating important predictors of new onset of hypertension. We investigated the predictive ability of several ML models for the development of hypertension.

Authors

  • Marenao Tanaka
    Department of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, Sapporo, Japan.
  • Yukinori Akiyama
    Department of Neurosurgery, Sapporo Medical University, Japan.
  • Kazuma Mori
    Department of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, Sapporo, Japan.
  • Itaru Hosaka
    Department of Cardiovascular Surgery, Sapporo Medical University School of Medicine, Sapporo, Japan.
  • Keisuke Endo
    Department of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, Sapporo, Japan.
  • Toshifumi Ogawa
    Department of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, Sapporo, Japan.
  • Tatsuya Sato
    Department of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, Sapporo, Japan.
  • Toru Suzuki
    Department of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, Sapporo, Japan.
  • Toshiyuki Yano
    Department of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, Sapporo, Japan.
  • Hirofumi Ohnishi
    Department of Public Health, Sapporo Medical University School of Medicine, Sapporo, Japan.
  • Nagisa Hanawa
    Keijinkai Maruyama Clinic, Sapporo, Japan.
  • Masato Furuhashi
    Department of Cardiovascular, Renal and Metabolic Medicine, Sapporo Medical University School of Medicine, Sapporo, Japan.

Keywords

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