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一个被拒绝的多omics整合框架用于癌症亚型分类和生存预测

Jiali Pang1, Bilin Liang1, Ruifeng Ding2

  • 1Shanghai Artificial Intelligence Laboratory, Shanghai, China.

Briefings in bioinformatics
|August 18, 2023
PubMed
概括

高通量测序数据有助于疾病的理解,但挑战机器学习. 我们的新多omics整合框架,AttentionMOI,具有特征选择与分布 (FSD),使用TCGA数据改善了癌症预后预测和亚型识别.

关键词:
人工智能的人工智能是人工智能.癌症亚型分类 癌症亚型分类多主题整合多主题整合.欧米克斯-数据的拒绝生存预测的预测.

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