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Updated: Jan 11, 2026

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
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基于机器学习的FFRCT用于冠状动脉疾病的诊断性能:元分析

Rui Lian1,2, Xiangmin Zhang3,4,5,6

  • 1Department of Gynecology and Obstetrics, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.

Open medicine (Warsaw, Poland)
|November 11, 2025
PubMed
概括

机器学习衍生微分流量储备计算断层扫描 (ML-FFRCT) 在诊断冠状动脉疾病 (CAD) 中显示出高准确性. 这种非侵入性工具显示出对CAD的临床评估有很大的潜力.

关键词:
在这里,我们可以看到CAD,CAD,CAD.美国FFRCT机器学习是机器学习.这里是Meta-Meta-Meta.

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