A dual-modal CNN system fuses CT and H&E features with clinical metadata to classify lung cancer subtypes at 0.87 accuracy and 0.97 AUROC, using multiple XAI methods for interpretability.
Nature511(7511), 543–550 (2014)
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Dual-Modal Lung Cancer AI: Interpretable Radiology and Microscopy with Clinical Risk Integration
A dual-modal CNN system fuses CT and H&E features with clinical metadata to classify lung cancer subtypes at 0.87 accuracy and 0.97 AUROC, using multiple XAI methods for interpretability.