breast cancer

We present a novel approach to temporal clustering of patient treatment information based on the semantic similarity of longitudinal histories.

We looked at registry-based data on breast cancer care at two neighboring healthcare institutions with a specific focus on whether organizational boundaries determine the physicians that a patient will see. From an initial patient-oriented data set, we developed a social network of physicians, modeling their interactions over the course of the provided treatments.