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Updated: Jan 10, 2026

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
06:16

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Published on: August 9, 2024

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优先考虑患有心脏病发作风险的患者,使用基于随机森林和决策树的全新全面目标ITARA

Niloofar Amini1, Sarfaraz Hashemkhani Zolfani2, Fausto Cavallaro3

  • 1Department of Industrial Engineering and Management Systems, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.

Scientific reports
|November 27, 2025
PubMed
概括

这项研究通过ITARA方法的机器学习提高了心脏病发作风险预测. 它通过基于冠状动脉疾病等关键预测因子,客观地优先考虑有风险的人来改善早期检测和临床管理.

关键词:
分类 分类 分类 分类.决策树 决策树是一个决策树.心脏病发作 心脏病发作基于冷漠度值的属性比率分析 (ITARA)机器学习是机器学习.多重标准的决策决策.随机的森林 随机的森林

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