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Updated: Jan 20, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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混合成像-临床模型用于预测肝细胞癌中的微血管入侵,使用来自CT的深度学习衍生的特征

Shidi Miao1, Mingxuan Wang1, Qi Dong1

  • 1School of Computer Science and Technology, Harbin University of Science and Technology, Harbin, China.

Physical and engineering sciences in medicine
|January 19, 2026
PubMed
概括

脂肪组织可以帮助预测肝癌患者的微血管入侵 (MVI). 一种使用深度学习和CT扫描的新混合模型显示,MVI诊断准确度有所提高,表现优于放射科医生.

关键词:
深度学习是一种深度学习.较小的奥门图层层.在MVI中,MVI就是MVI.多式联络是多式联络.总体生存率 总体生存率

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