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

doi:10.1177/22104917221082315

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 publication › Review article › Academic research › peer-review

3 Citations (Scopus)

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.

Original language	English
Journal	Journal of Orthopaedics, Trauma and Rehabilitation
Volume	29
Issue number	1
DOIs	https://doi.org/10.1177/22104917221082315
Publication status	Published - Jun 2022

Keywords

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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10.1177/22104917221082315

Cite this

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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.",

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author = "Yick, {Hin Ting Victor} and Chan, {Ping Keung} and Chunyi Wen and Fung, {Wing Chiu} and Yan, {Chun Hoi} and Chiu, {Kwong Yuen}",

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AU - Fung, Wing Chiu

AU - Yan, Chun Hoi

AU - Chiu, Kwong Yuen

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AB - 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.

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

Abstract

Keywords

ASJC Scopus subject areas

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