PATH gene embeddings in a graph transformer achieve 0.8766 F1 on pancancer metastasis prediction (8.8% over SOTA) and identify disease-state pathway rewiring.
H.et al.PathCNN: interpretable convolutional neural networks for survival prediction and pathway analysis applied to glioblastoma.Bioinformatics37, i443–i450 (2021)
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Graph Transformer-Based Pathway Embedding for Cancer Prognosis
PATH gene embeddings in a graph transformer achieve 0.8766 F1 on pancancer metastasis prediction (8.8% over SOTA) and identify disease-state pathway rewiring.