Exploring long-term breast cancer survivors' care trajectories using dynamic time warping-based unsupervised clustering.

The results could provide the basis for better understanding the BCS' circulation through the health system, with a view to more efficiently predicting their forthcoming needs and thus designing more effective personalized survivorship care plans.