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Updated: Jul 22, 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

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[基于自我监督的预训和多任务学习的肺腺癌无复发生存率的预测]

Lunyu Hu1,2, Wei Xia1,2, Qiong Li3

  • 1School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230026, P. R. China.

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
|April 30, 2024
PubMed
概括

这项研究引入了一种新的AI方法,使用计算机断层扫描 (CT) 成像和多任务学习来预测肺腺癌患者的无复发生存率 (RFS),优于现有方法.

关键词:
计算机断层扫描 (CT) 是一种计算机断层扫描.肺部腺癌是肺部的癌症.多任务学习多任务学习手术后复发的情况自主监督学习学习

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