Cancer Registry

Cancer registries are crucial for collecting, validating, and analyzing cancer data to inform research and public health initiatives. Current research emphasizes improving data management through automated systems and leveraging machine learning, particularly transformer-based models like BERT and LLMs, to enhance data extraction, validation, and analysis from diverse sources like clinical notes and research literature. This work aims to improve the accuracy, efficiency, and interpretability of cancer registry data, ultimately leading to better cancer prevention, diagnosis, and treatment strategies.