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Updated: Jul 15, 2025

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基于注意力的生成对抗网络改善了从多式联络数据中预测癌症的预后结果

Mingguang Shi1, Xuefeng Li1, Mingna Li1

  • 1School of Electrical Engineering and Automation, Hefei University of Technology, Hefei, Anhui 230009, China.

Briefings in bioinformatics
|September 27, 2023
PubMed
概括

本研究介绍了CSAM-GAN,这是一种深度学习方法,用于使用多式联络数据预测癌症预后结果. 它有效地整合和选择特征,改善癌症分层和个性化医疗.

关键词:
生成性的对抗性网络.多式联运数据是多式联运数据.预后结果预测预测结果预测.连续的频道空间注意模块.

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