Machine learning models for dementia screening to classify brain amyloid positivity on positron emission tomography using blood markers and demographic characteristics: a retrospective observational study.

Journal: Alzheimer's research & therapy
PMID: 39838434

Abstract

BACKGROUND: Intracerebral amyloid β (Aβ) accumulation is considered the initial observable event in the pathological process of Alzheimer's disease (AD). Efficient screening for amyloid pathology is critical for identifying patients for early treatment. This study developed machine learning models to classify positron emission tomography (PET) Aβ-positivity in participants with preclinical and prodromal AD using data accessible to primary care physicians.

Authors

  • Noriyuki Kimura
    Department of Neurology, Faculty of Medicine, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu, Oita, 879-5593, Japan. noriyuki@oita-u.ac.jp.
  • Kotaro Sasaki
    Human Biology Integration Foundation, Deep Human Biology Learning, Eisai Co., Ltd, 4-6-10 Koishikawa, Bunkyo-ku, Tokyo, 112-8088, Japan. k10-sasaki@hhc.eisai.co.jp.
  • Teruaki Masuda
    Department of Neurology, Faculty of Medicine, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu, Oita, 879-5593, Japan.
  • Takuya Ataka
    Department of Neurology, Faculty of Medicine, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu, Oita, 879-5593, Japan.
  • Mariko Matsumoto
    Neurology Department, Medical Headquarters, Eisai Co., Ltd, 3-7-1 Nishi Shinjuku, Shinjuku-ku, Tokyo, 163-1023, Japan.
  • Mika Kitamura
    Neurology Department, Medical Headquarters, Eisai Co., Ltd, 3-7-1 Nishi Shinjuku, Shinjuku-ku, Tokyo, 163-1023, Japan.
  • Yosuke Nakamura
    Neurology Department, Medical Headquarters, Eisai Co., Ltd, 3-7-1 Nishi Shinjuku, Shinjuku-ku, Tokyo, 163-1023, Japan.
  • Etsuro Matsubara
    Department of Neurology, Faculty of Medicine, Oita University, 1-1 Idaigaoka, Hasama-machi, Yufu, Oita, 879-5593, Japan.

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