Applications of deep learning in total knee arthroplasty: a scoping review

Total knee arthroplasty (TKA) is a highly successful procedure for end-stage knee osteoarthritis, yet challenges persist in achieving optimal and consistent outcomes. These include inaccuracies in preoperative planning, subjective intraoperative decision-making, and variability in postoperative assessment. Deep learning (DL), a subset of artificial intelligence, has shown transformative potential in medical image analysis and predictive modeling. Its application in TKA is rapidly emerging across the entire patient care pathway. This project outlines the protocol for a scoping review that aims to systematically map the existing literature on the application of DL in TKA. The primary objective is to provide a comprehensive overview of the current landscape, identifying the breadth of applications, commonly used methodologies, and key research gaps. Unlike a systematic review focused on efficacy, this scoping review will chart the field's scope, clarifying concepts and evidence types.