Generative AI Enhances Precision Oncology Workflows

A narrative review by Hamamoto et al., published in the Journal of Hematology & Oncology (2026), synthesizes literature on integrating generative AI into precision oncology, assessing LLMs and VLMs for interpreting genomic variants, matching patients to clinical trials, and drafting integrated diagnostic reports. The authors cite validated examples (TrialGPT: 87.3% accuracy, 42.6% faster; Flamingo‑CXR: diagnostic parity or superiority in 77.7% cases) and recommend RAG grounding, human-in-the-loop oversight, and rigorous validation before clinical deployment.