Keywords: Osteoarthritis, Machine Learning/Artificial Intelligence, Deep LearningWe propose a novel risk constraint to improve the performance of deep learning models on progressive disorders. On the Osteoarthritis Initiative (OAI) dataset, the proposed approach outperforms a baseline model trained with the standard cross-entropy loss on predicting total knee replacement (TKR) within 3 different time horizons- 1 year, 2 years and 4 years of the MRI date. It further generalizes better to the external Multicenter Osteoarthritis Study dataset.
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