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以临床结果为指导的深度时聚类用于疾病进展亚型化

Dulin Wang1, Xiaotian Ma1, Paul E Schulz2

  • 1McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.

Journal of biomedical informatics
|October 2, 2024
PubMed
概括

这项研究引入了一个新的框架,用于对复杂疾病进行聚类,根据疾病进展和临床结果确定不同的患者亚型. 该方法通过揭示子组变异来增强个性化治疗策略.

关键词:
集群验证验证 集群验证深度表示学习学习 (Deep Representation Learning) 是一种学习方式.疾病进展 亚型化 疾病进展时间集群时间集群

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