Hin Ting Victor Yick, P. Chan, Chunyi Wen, W. C. Fung, C. Yan, K. Chiu
{"title":"Artificial intelligence reshapes current understanding and management of osteoarthritis: A narrative review","authors":"Hin Ting Victor Yick, P. Chan, Chunyi Wen, W. C. Fung, C. Yan, K. Chiu","doi":"10.1177/22104917221082315","DOIUrl":null,"url":null,"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.","PeriodicalId":42408,"journal":{"name":"Journal of Orthopaedics Trauma and Rehabilitation","volume":"18 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2022-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Orthopaedics Trauma and Rehabilitation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/22104917221082315","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ORTHOPEDICS","Score":null,"Total":0}
引用次数: 0
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.