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Updated: Jul 20, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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冠状动脉干预后并发症的机器学习模型的预测性能:系统审查和元分析

Soroush Najdaghi1, Delaram Narimani Davani2, Davood Shafie2

  • 1Heart Failure Research Center, Cardiovascular Research Institute, Isfahan University of Medical Science, Isfahan, Iran. Soroush.najdaghi@yahoo.com.

International urology and nephrology
|October 31, 2024
PubMed
概括

机器学习模型在心脏手术后有效预测急性损伤 (AKI) 和对比诱导的病 (CIN). 梯度增强机和支向量机模型显示了最有前途的早期检测和干预.

关键词:
急性损伤是什么?急性损伤是什么?对比诱导的脏病.机器学习是机器学习.进行元分析分析.通过皮肤进行冠状动脉干预.系统性审查 系统性审查

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