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Updated: Aug 7, 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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一种自编码器学习方法,用于预测乳腺癌亚型

Zahra Rostami1, Kavitha Mukund2, Maryam Masnadi-Shirazi3

  • 1Department of Computer Science and Engineering, University of California San Diego, San Diego, California, United States of America.

PloS one
|July 23, 2025
PubMed
概括

这项研究引入了一种自编码模型,用于识别乳腺癌亚型的关键基因标记物. 该模型准确地描述了亚型,有助于检测和理解独特的癌症机制.

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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...