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Updated: Jun 19, 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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清细胞细胞癌治疗结果预测的多式组合方法

Meixu Chen1, Kai Wang1,2, Payal Kapur3

  • 1Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 75235, USA.

ArXiv
|December 23, 2024
PubMed
概括

这项研究引入了一种多模组合模型 (MMEM) 用于清细胞细胞癌 (ccRCC) 预后,整合了临床,多omics和整个幻灯片图像 (WSI) 数据. 与单个数据类型模型相比,MMEM显著改善了总生存率 (OS) 和无疾病生存率 (DFS) 的预测.

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Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...