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Artificial intelligence in orthopaedics: Enhanced examinations, ambient intelligence and the future of clinical practice

  • Alexander Bouterse
  • , James A. Pruneski
  • , Felix C. Oettl
  • , Balint Zsidai
  • , Thomas Tischer
  • , Umile Giuseppe Longo
  • , Romain Seil
  • , Michael T. Hirschmann
  • , Kristian Samuelsson*
  • *Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Artificial intelligence (AI) continues to rapidly transform the practice of medicine, with clinicians increasingly adopting data-driven decision-making aids and diagnostic support tools. Orthopaedic physicians are well poised to harness the capabilities of AI, with an abundance of quantifiable imaging, biomechanical data, and structured clinical parameters lending themselves to algorithmic interpretation and automation. Namely, AI-augmented vision systems may increase the breadth of information readily available to clinicians, whereas smart exam rooms and automated clinical summaries may soon streamline clinical workflows to decrease administrative burden and allow more time for direct patient care. Personalised education materials and visual aids may improve patient understanding and compliance, with the aim of optimising patient outcomes. Generative medical and orthopaedic event models may soon alter decision-making heuristics and improve patient counselling. While the widespread adaptation of AI into clinical practices is not without limitations, physicians will likely come to share an increasingly symbiotic relationship with these platforms throughout their continued evolution. Accordingly, it is imperative that current and future orthopaedic practitioners become well-versed in harnessing the capabilities of AI and continue to identify new avenues for such technologies to benefit clinicians and patients alike. As such, the current manuscript provides a narrative review of the potential future applications of AI within orthopaedic practices by exploring current and developing technologies and detailing how the continued integration of AI-powered systems may serve to revolutionise the delivery of orthopaedic care. Level of Evidence: Level V.

Original languageEnglish
Pages (from-to)1901-1909
Number of pages9
JournalKnee Surgery, Sports Traumatology, Arthroscopy
Volume34
Issue number5
DOIs
Publication statusPublished - May 2026
Externally publishedYes

Keywords

  • artificial intelligence
  • deep learning
  • machine learning
  • orthopaedics
  • Humans
  • Artificial Intelligence
  • Orthopedics/trends

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