Editorial discusses AI's role in enhancing implant design and surgical precision in arthroplasty, stressing important challenges.
Artificial intelligence (AI) is rapidly transforming hip and knee arthroplasty, particularly in the areas of pre-operative planning and implant design. By integrating advanced imaging analysis, machine learning algorithms, and data-driven analytics, AI-enabled technologies have the potential to enhance surgical precision, improve implant selection, and facilitate consistent restoration of joint biomechanics. AI-based planning systems can automate the analysis of radiographic and three-dimensional imaging data, enabling more accurate prediction of implant size, alignment, and anatomical landmarks compared with conventional templating. Robotic and navigation-assisted platforms further extend these capabilities by providing real-time intraoperative guidance, improving the accuracy and reproducibility of implant positioning while maintaining surgeon control. In addition, advances in generative design and computational modeling are enabling the development of patient-specific implants and biomechanically optimized implant geometries. Despite these advances, challenges related to data quality, algorithmic bias, interpretability, cost, ethical concerns, and regulatory oversight remain. This editorial discusses the current applications, benefits, and limitations of AI in arthroplasty and highlights the need for rigorous validation and responsible integration, emphasizing that AI should complement rather than replace surgical expertise.
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Aneja et al. (2026) studied this question.
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