Amyloid-β prediction machine learning model using source-based morphometry across neurocognitive disorders

Abstract Previous studies have developed and explored magnetic resonance imaging (MRI)-based machine learning models for predicting Alzheimer’s disease (AD). However, limited research has focused on models incorporating diverse patient populations. This study aimed to build a clinically useful predi...

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書誌詳細

主要な著者:	Yuki Momota, Shogyoku Bun, Jinichi Hirano, Kei Kamiya, Ryo Ueda, Yu Iwabuchi, Keisuke Takahata, Yasuharu Yamamoto, Toshiki Tezuka, Masahito Kubota, Morinobu Seki, Ryo Shikimoto, Yu Mimura, Taishiro Kishimoto, Hajime Tabuchi, Masahiro Jinzaki, Daisuke Ito, Masaru Mimura
フォーマット:	Artigo
言語:	Inglês
出版事項:	Nature Portfolio 2024-04-01
シリーズ:	Scientific Reports
主題:	Alzheimer’s disease Amyloid-β Machine learning Magnetic resonance imaging Source-based morphometry
オンライン･アクセス:	https://doi.org/10.1038/s41598-024-58223-3
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