Prediction of Peripheral Artery Disease Treatment Decisions and Outcomes Using Machine Learning and Gait-Derived Digital Biomarkers
Background: Peripheral artery disease (PAD) is clinically heterogeneous, complicating identification, treatment selection, and prediction of therapeutic benefit. Gait biomechanics provide high-resolution, objective digital biomarkers that can be used in routine care. Methods: We built a computational framework for thre...