Artificial Intelligence in Total Hip and Knee Arthroplasty: A Primer on Current Applications, Algorithms, and Future Directions

» Artificial intelligence (AI) is increasingly integrated across the total hip and knee arthroplasty care continuum, including preoperative risk stratification and templating, intraoperative computer-vision guidance and robotic assistance, and postoperative complication detection and outcome prediction. » Machine-learning models often outperform traditional statistical approaches in predicting complications, discharge disposition, operative time, and patient-reported outcomes after total joint arthroplasty. » Deep learning and computer vision systems are rapidly improving radiographic interpretation, implant templating, mechanical alignment measurement, and early detection of prosthetic loosening. » Despite promising performance, most AI tools remain limited by incomplete external validation, workflow integration challenges, and potential bias from nonrepresentative data sets. » Future progress in arthroplasty AI will depend on multimodal data integration, large-scale registries, prospective validation, and careful collaboration between surgeons and data scientists to ensure safe and clinically meaningful implementation.