原因病変の診断と急性冠動脈症候群のリスク評価を統合した人工知能モデル

Peng Peng Xu1, Bin Hu1, Fan Zhou1

  • 1Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, 210002, China.

EClinicalMedicine
|August 20, 2025
PubMed
まとめ

ランダムフォレスト (RF) モデルは,急性冠動脈症候群 (ACS) の原因病変を正確に診断し,最大2年間の将来のACSリスクを予測しました. この機械学習アプローチは 心血管リスクの階層化を改善します

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