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Artificial intelligence in shoulder arthroplasty: latest concepts and clinical integration
Young Dae Jeon1, Jaemin Oh1, Ki-Bong Park1
1Department of Orthopaedic Surgery, University of Ulsan College of Medicine, Ulsan University Hospital, Ulsan, South Korea.
Journal of Orthopaedic Surgery and Research
|July 9, 2026
Summary
Artificial intelligence (AI) enhances shoulder arthroplasty diagnostics and planning but has not yet improved patient outcomes. Further development and surgeon trust are crucial for safe AI integration in surgery.
Area of Science:
- Orthopedic Surgery
- Artificial Intelligence
- Medical Technology
Background:
- Artificial intelligence (AI) advances shoulder arthroplasty, improving diagnostics, surgical planning, and recovery.
- Despite technical promise, AI has not yet demonstrated improved routine surgical or patient outcomes in shoulder arthroplasty.
Purpose of the Study:
- To review state-of-the-art AI applications in shoulder arthroplasty.
- To highlight AI strengths, limitations, and integration strategies.
- To align technological innovation with surgical expertise.
Main Methods:
- Review of AI applications in shoulder arthroplasty, covering preoperative, intraoperative, and postoperative phases.
- Analysis of deep learning imaging, 3D reconstruction, robotic assistance, and machine learning prognostic models.
- Exploration of emerging innovations like mixed reality and explainable AI.
Main Results:
- AI demonstrates strong diagnostic performance for rotator cuff tears and arthritis.
- AI assists in preoperative planning, component placement precision, and postoperative monitoring.
- Current AI lacks surgeon intuition; explainable AI and multimodal integration aim to bridge this gap.
Conclusions:
- Surgeon adoption of AI depends on demonstrated reliability across diverse settings.
- Technical refinement, surgeon trust, and regulatory frameworks are essential for safe AI integration.
- Inadequate validation or implementation may increase costs, complexity, or delay care.