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Updated: Jan 16, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
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HSFSurv:在个人和特征层面的混合监督框架,用于多模式癌症存活率分析

Bangkang Fu1, Junjie He2, Xiaoli Zhang3

  • 1Medical College, Guizhou University, Guiyang, 550025, Guizhou, China; Guizhou Province International Science and Technology Cooperation Base for Precision Imaging Diagnosis and Treatment, Key Laboratory of Advanced Medical Imaging and Intelligent Computing of Guizhou Province, Department of Radiology, Guizhou Provincial People's Hospital, Guiyang, 550002, Guizhou, China.

Medical image analysis
|September 28, 2025
PubMed
概括

这项研究引入了多式生存分析的新型混合框架,有效地整合了各种数据类型,如病理学和基因组学. 该方法通过解决数据异质性来改善癌症结果分析,从而提高预后预测.

关键词:
癌症生存率分析分析数据融合数据融合深度学习是一种深度学习.数字病理学数字病理学多式联络是多式联络.

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