Cutting-edge AI, genomic, and molecular diagnostic advances are reshaping cancer care. Transformer models combined with radiomic data now predict cervical cancer prognosis with enhanced accuracy. Geisinger’s genomic-first approach identified rare pathogenic variants in over 2.5% of a large cohort, many undiagnosed clinically. Multi-domain imaging biomarkers improve lung cancer subtype classification, refining diagnostics. These innovations herald improved personalized treatment strategies and expand understanding of cancer biology.