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Updated: May 5, 2026

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机器学习方法用于预测非洲慢性乙型肝炎的疾病进展

Hailemichael Desalegn1,2, Xianchen Yang3,4, Yi-Syuan Yen3,5

  • 1Medical Department, St. Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia.

Hepatology communications
|January 8, 2025
PubMed
概括

在非洲患者中预测慢性乙型肝炎 (HBV) 感染进展至关重要. 使用标准实验室测试的机器学习模型对识别患有HBV疾病进展风险的患者显示出有前途.

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In clinical practice, the direct measurement of hepatic blood flow to evaluate liver function presents significant challenges due to the intricate and specialized nature of the necessary techniques. Consequently, healthcare professionals often rely on empirical estimates derived from thorough patient examinations and liver function tests to gauge liver health. Among the tools at their disposal, the Child–Pugh and MELD scoring systems stand out for their ability to categorize and assess...
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