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Updated: Sep 11, 2025

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

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[基于机器学习算法构建化学疗法诱导的乳腺癌患者心脏毒性风险预测模型]

X N Yue1, C Yan2, X Y Liu3

  • 1School of Public Health, Xinjiang Medical University, Urumqi 830054, China Information Management and Big Data Center, Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi 830000, China.

Zhonghua xin xue guan bing za zhi
|August 18, 2025
PubMed
概括

机器学习模型可以预测乳腺癌患者接受 antracycline 化疗的心血管毒性. 随机森林模型在识别患有心电图异常风险的患者方面表现最好.

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Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
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