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Updated: Jan 30, 2026

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CLinNET:一个可解释和不确定性意识的深度学习框架,用于多模式临床基因组学.

Ivan Bakhshayeshi1, Mohammad Mahdi Hosseini2, Ahmadreza Argha3,4

  • 1UNSW BioMedical Machine Learning Lab (BML), School of Biomedical Engineering, UNSW Sydney, Sydney, NSW, 2052, Australia.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
|January 28, 2026
PubMed
概括

一个人工智能工具CLinNET通过解释具有不确定的意义的变异来改善神经认知障碍基因识别. 这种可解释的深度学习模型提高了诊断的准确性,并识别了与疾病相关的新型基因.

关键词:
副本编号变体 副本编号变体深度学习是一种深度学习.基因修复 基因修复可以解释的解释性.神经认知障碍 神经认知障碍不确定性量化不确定性量化

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