A Clinically Interpretable Multimodal Framework for Severity-Aware Lung Cancer Diagnosis via Bidirectional Fusion, Graph Transformer Networks, and Generative Learning
Clinically interpretable lung cancer diagnosis remains a critical challenge in computational oncology, particularly when severity-aware staging demands the integration of heterogeneous imaging and clinical data. Existing deep learning approaches either operate on single modalities with limited clinical context or emplo...