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一个具有增强特征表示的多模式融合模型,用于预测慢性病进展

Yixuan Qiao1,2, Hong Zhou3, Yang Liu1,2

  • 1Institute of Computing Technology, Chinese Academy of Sciences (ICT), 6 Kexueyuan Nanlu, Zhongguancun, Haidian, Beijing 100190, China.

Briefings in bioinformatics
|February 6, 2025
PubMed
概括

一个AI模型DeepOmix-FLEX通过专注于特征表示来增强多模式数据融合. 这种方法改善了慢性病进展的预测,优于传统方法.

关键词:
慢性脏疾病 慢性脏疾病计算病理学计算病理学深度学习是一种深度学习.多式联运是多式联运.多种主题的多种主题.进展的预测和预测.

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