Dataset dependency of low-density lipoprotein-cholesterol estimation by machine learning.

Journal: Annals of clinical biochemistry
PMID: 37218090

Abstract

OBJECTIVES: We evaluated the applicability of a machine learning-based low-density lipoprotein-cholesterol (LDL-C) estimation method and the influence of the characteristics of the training datasets.

Authors

  • Ishida Hidekazu
    Department of Clinical Laboratory, Fujita Health University Hospital, Toyoake, Japan.
  • Hiroki Nagasawa
    Department of Chemical Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashihiroshima 739-8527, Japan.
  • Yasuko Yamamoto
    Department of Disease Control and Prevention, Fujita Health University Graduate School of Health Sciences, Toyoake, Japan.
  • Hiroki Doi
    Department of Clinical Laboratory, Fujita Health University Hospital, Toyoake, Japan.
  • Midori Saito
    Department of Clinical Laboratory, Fujita Health University Hospital, Toyoake, Japan.
  • Yuya Ishihara
    Department of Clinical Laboratory, Fujita Health University Hospital, Toyoake, Japan.
  • Takashi Fujita
    Department of Urology, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Mariko Ishida
    Division of Clinical Laboratory, Gifu University Hospital, Gifu, Japan.
  • Yohei Kato
    Division of Clinical Laboratory, Gifu University Hospital, Gifu, Japan.
  • Ryosuke Kikuchi
    Division of Clinical Laboratory, Gifu University Hospital, Gifu, Japan.
  • Hidetoshi Matsunami
    Matsunami Research Park, Japan.
  • Masao Takemura
    Department of Disease Control and Prevention, Fujita Health University Graduate School of Health Sciences, Toyoake, Japan.
  • Hiroyasu Ito
    Department of Clinical Laboratory, Fujita Health University Hospital, Toyoake, Japan.
  • Kuniaki Saito
    Graduate School of Health Sciences, Fujita Health University, 1-98 Dengakugakubo, Kutsukake cho, Toyoake City, Aichi, 470-1192, Japan.

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