Development and validation of machine learning risk prediction models for detection of Early-Onset Colorectal Cancer: Data from 30 health systems in the United States
Date:
Lau, W., Kim, Y. , Parasa, S., Haque, M. E., Darai, S., Rao, R., Pillai, J., Oka, A. (2025, May)
Incidence of early-onset colorectal cancer (EoCRC) in patients without any family history has been increasing in recent years. Our study leveraged advanced Large Language Models (LLM), like GPT-4, to predict EoCRC in a population comprised of multiple health systems across the United States. There is potential to improve patient care by suggesting early screening for patients who are predicted to be at risk by the model.