From screening to subtyping in a single glance.

Fragmented AI tools struggle with the complex diagnosis of fine-grained diseases from radiological images. A new study in Patterns introduces the "screening-to-subtyping" (S2S) framework, a holistic deep learning system integrating the entire diagnostic workflow from detection to subtyping. Validated on complex thoracic cancers, the S2S-Med system demonstrated superior accuracy, outperforming existing benchmarks. A human-AI experiment revealed that the AI's performance surpassed AI-assisted physicians and that physician trust correlated with greater improvement. The S2S framework is a significant step toward enhancing precision medicine and establishing a new paradigm for human-AI partnership.