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Updated: Feb 14, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

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机器学习驱动的个性化风险预测:为患有关节炎的老年欧洲成年人开发一种可解释的肉病模型

Xiao Xu1,2

  • 1Research Center of Molecular Medicine (PhD Lab), Faculty of Nursing, Nantong Health College of Jiangsu Province, Nantong 226001, China.

Journal of clinical medicine
|February 13, 2026
PubMed
概括

这项研究开发了一种可解释的机器学习模型,使用9个关键指标预测老年关节炎患者的肉症风险. 该模型为有针对性的干预提供了精确的早期查.

关键词:
关节炎是一种关节炎.机器学习是机器学习.这种类型的麻症是sarcopenia.

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