P088: Leveraging OpenAI GPTs for precision oncology: A custom guideline-constrained model in hereditary cancer

Effective management of hereditary cancer requires integrating evolving genetic evidence, risk models, and surveillance recommendations across various syndromes. The National Comprehensive Cancer Network (NCCN) guidelines for hereditary cancer are comprehensive but are updated frequently and can be complex to navigate in clinical settings. Healthcare providers often face challenges in accessing and interpreting these guidelines at the point of care, leading to inconsistent management practices. While Large language models (LLMs) have demonstrated potential to summarize complex medical information, they can also hallucinate, omit critical details, or generate non–guideline-concordant responses.