機械学習アプローチによるリスクの高いMASHの正確な同定を可能にする
Masaya Sato1,2, Takuma Nakatsuka1, Tatsuya Minami1
1Department of Gastroenterology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
まとめ
新しい機械学習モデルは、日常的な臨床データを使用して、リスクの高い代謝機能障害関連肝硬化(MASH)を正確に特定します。この非侵襲的なアプローチは、進行した肝疾患を予測するための肝硬度測定に代わる費用対効果の高い代替法を提供します。
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