Thousands of articles on breast cancer are published every year. We show how combining automated strategies to identify clinically relevant and surrogate survivorship outcomes can be combined with explicit claims from the Claim Framework to show how survivorship outcomes have changed over time. Our goal is to automatically extract and model existing treatments in order to better detect promising new breast cancer treatment strategies as they emerge in the literature.

Learning Objective: Participants will learn how automated strategies to detect surviorship outcomes from text can be combined with the Claim Framework to trace how survivorship outcomes have changed for different treatments over time.


Catherine Blake (Presenter)
University of Illinois

Presentation Materials: