Total Knee Replacement

Total knee replacement (TKR) prediction is a burgeoning field leveraging machine learning to improve diagnosis and treatment planning. Current research heavily utilizes deep learning models, particularly transformer-based architectures and other neural networks, to analyze diverse data sources including MRI images, gait analysis data (e.g., knee joint angles), and even wearable sensor information to predict the need for TKR. These advanced models aim to improve prediction accuracy and enable more personalized approaches to patient care. The ultimate goal is to enhance the efficiency and effectiveness of TKR procedures, leading to better patient outcomes and optimized resource allocation within healthcare systems.