Deep Learning for Predicting Progression of Patellofemoral Osteoarthritis Based on Lateral Knee Radiographs, Demographic Data and Symptomatic Assessments
Objective: In this study, we propose a novel framework that utilizes deep learning and attention mechanisms to predict the radiographic progression of patellofemoral osteoarthritis (PFOA) over a period of seven years. Design: This study included subjects (1832 subjects, 3276 knees) from the baseline of the Multicenter Osteoarthritis Study (MOST). Patellofemoral joint regions-of interest were ident