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Updated: Sep 17, 2025

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一个基于机器学习的框架,用于使用血清肝功能测试和高灵敏度C反应蛋白预测代谢综合征.

Bahareh Behkamal1,2, Fatemeh Asgharian Rezae2, Amin Mansoori3

  • 1Medicinal Chemistry Department, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, 9177899191, Iran.

Scientific reports
|July 2, 2025
PubMed
概括

机器学习模型使用肝功能测试和hs-CRP准确预测代谢综合征 (MetS). 渐变增强和CNN显示出高特异性,使得早期,非侵入性的MetS检测.

关键词:
高灵敏度C反应蛋白 (hs-CRP) 是一种高灵敏度C反应蛋白.肝功能测试是肝功能测试.机器学习 机器学习代谢综合征是代谢综合征.

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Cardiac biomarkers are critical in diagnosing, prognosing, and managing cardiovascular diseases. Routine measurement of specific biomarkers such as B-type natriuretic peptide (BNP), C-reactive protein (CRP), and homocysteine (Hcy) is common practice in clinical settings to evaluate heart function and predict cardiovascular events.
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