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Updated: Jan 13, 2026

Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis
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在健康男性中使用可解释机器学习发现血清尿酸生物标志物的非线性预测因子

Chung-Chi Yang1,2,3,4, Min-Chung Shen5, Zih-Yin Lai3,4

  • 1Division of Cardiology, Department of Medicine, Taoyuan Armed Forces General Hospital, Taoyuan 325208, Taiwan.

Biomedicines
|October 29, 2025
PubMed
概括

多变量自适应回归线 (MARS) 揭示了尿酸 (UA) 与腰比,肌素,,hs-CRP 和在健康男性中使用贝特尔坚果之间的非线性联系,提供了精确的临床风险见解.

关键词:
机器学习是机器学习.多重线性回归的多重线性回归.多变量自适应回归线 (splines) 是多变量自适应回归线.非线性建模非线性建模尿酸是什么 尿酸是什么 尿酸是什么

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