Artificial intelligence reshapes current understanding and management of osteoarthritis: A narrative review

Hin Ting Victor Yick, Ping Keung Chan, Chunyi Wen, Wing Chiu Fung, Chun Hoi Yan, Kwong Yuen Chiu

Research output: Journal article publicationReview articleAcademic researchpeer-review


Current practice of osteoarthritis has its insufficiencies which researchers are tackling with artificial intelligence (AI). This article discusses three kinds of AI models, namely diagnostic models, prediction models and morphological models. Diagnostic models enhance efficiency in diagnosis by providing an automated algorithm in knee images processing. Prediction models utilize behavioral and radiological data to assess the risk of osteoarthritis before symptom onset and needs to perform surgery. Morphological models detect biomechanical changes to facilitate understanding of pathophysiology and provide personalized intervention. Through reviewing present evidence, we demonstrate that AI could assist doctors in diagnosis, predict osteoarthritis and guide future research.

Original languageEnglish
JournalJournal of Orthopaedics, Trauma and Rehabilitation
Issue number1
Publication statusPublished - Jun 2022


  • Artificial intelligence
  • deep learning
  • machine learning
  • osteoarthritis

ASJC Scopus subject areas

  • Orthopedics and Sports Medicine
  • Physical Therapy, Sports Therapy and Rehabilitation
  • Rehabilitation

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