SMILESGNN: Interpretable Clinical Toxicity Prediction via SMILES-Graph Cross-Attention Fusion

T1Covered by 1 source · first reported by arXiv at 25 Sept, 04:00 UTC

arXiv:2609.28553v1 Announce Type: cross Abstract: Drug toxicity prediction is critical for reducing late-stage attrition in drug discovery, yet remains challenging due to severe class imbalance, scaffold-based generalization, and the clinical need for interpretable predictions. Single-modality…

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• T1SMILESGNN: Interpretable Clinical Toxicity Prediction via SMILES-Graph Cross-Attention FusionarXiv25 Sept, 04:00