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Updated: Jul 23, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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机器学习可以根据传统的风险因素,冠状动脉和心上脂肪体积预测血液动力学显著的CAD

Wenji Yu1, Le Yang1, Feifei Zhang1

  • 1Department of Nuclear Medicine, The Third Affiliated Hospital of Soochow University, Institute of Clinical Translation of Nuclear Medicine and Molecular Imaging, Soochow University, No.185, Juqian Street, Changzhou, 213003, Jiangsu, China.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
|July 11, 2023
PubMed
概括

一个可解释的机器学习模型有效地使用传统的风险因素,冠状动脉 (CAC) 和心上脂肪体积 (EFV) 选出血动力学显著的冠状动脉疾病 (CAD). 这种方法提供了高度准确的个性化风险预测.

关键词:
冠状动脉疾病是一种冠状动脉疾病.冠状动脉 冠状动脉胸前脂肪组织的脂肪组织.机器学习是机器学习.心肌缺血症的心肌缺血症是什么

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