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Title: Artificial intelligence reshapes current understanding and management of osteoarthritis : a narrative review
Authors: Yick, HTV
Chan, PK
Wen, C 
Fung, WC
Yan, CH
Chiu, KY
Issue Date: Jun-2022
Source: Journal of orthopaedics, trauma and rehabilitation, June 2022, v. 29, no. 1, p. 1-8
Abstract: 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.
Keywords: Artificial intelligence
Machine learning
Osteoarthritis
Deep learning
Publisher: Sage Publications Ltd.
Journal: Journal of orthopaedics, trauma and rehabilitation 
ISSN: 2210-4917
EISSN: 2210-4925
DOI: 10.1177/22104917221082315
Rights: © The Author(s) 2022
Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
The following publication Yick, H. T. V., Chan, P. K., Wen, C., Fung, W. C., Yan, C. H., & Chiu, K. Y. (2022). Artificial intelligence reshapes current understanding and management of osteoarthritis: A narrative review. Journal of Orthopaedics, Trauma and Rehabilitation, 29(1), 1-8 is available at https://doi.org/10.1177/22104917221082315.
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