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Updated: Jun 27, 2026

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高精度的疾病诊断和高度可复制的生物标志物识别与PathFormer

Zehao Dong1, Qihang Zhao2, Philip R O Payne3

  • 1Department of Computer Science & Engineering, Washington University in St. Louis, St. Louis, MO, USA.

Research square
|November 28, 2023
PubMed
概括

一种新型图形神经网络 (GNN) 模型PathFormer提高了疾病诊断的准确性和生物标记物识别可重现性. 这种新方法在复杂的生物途径数据上显著改进了现有的GNN模型.

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