Author

J. Su

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#explainable ai Open access Sep 2026

PCGS: biomarker and risk group identification for Pediatric Cancers via explainable Graph neural networks with Shapley values

This framework outperforms previous supervised multi-omics integration baseline approaches based on glioma and Wilms tumor cohorts and enables GNN model explainability via Shapley value-based feature attribution approaches to explain the contributions of gene-level features across various biomedical tasks, including classification and survival.

Z. Shi, A. Budhkar, W. Amin et al. · medRxiv · 0 citations

Review Open access Aug 2026

Evaluating Eight Retrieval-Augmented Generation (RAG) Large Language Models' Responses to Clinical Questions: A Comparative Study

It is suggested that RAG LLMs may be supplementary tools for evidence retrieval and synthesis but cannot, at this time, fully replace comprehensive expert review of the medical literature.

P. A. Krump, Mallory N. Blasingame, T. Koonce et al. · medRxiv · 0 citations