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Updated: Jul 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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患有结肠直肠癌的风险分层患者使用基于深度学习的预后生物标志物是否具有成本效益?

Anna Kenseth1, Dominika Kantorova1, Mikyung Kelly Seo2,3,4

  • 1Institute for Cancer Genetics and Informatics, Oslo University Hospital, Oslo, Norway.

PharmacoEconomics
|April 7, 2024
PubMed
概括

基因型鉴定是一种深度学习方法,为挪威的结直肠癌 (CRC) 风险分层提供了一种具有成本效益的策略. 这种方法优化了辅助化疗的分配,改善了CRC患者的健康结果和资源管理.

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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...