{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T10:02:19Z","timestamp":1790848939367,"version":"4.1.0"},"reference-count":84,"publisher":"Elsevier BV","issue":"3","license":[{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T00:00:00Z","timestamp":1740787200000},"content-version":"vor","delay-in-days":365,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","oarsijournal.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Osteoarthritis and Cartilage"],"published-print":{"date-parts":[[2024,3]]},"DOI":"10.1016\/j.joca.2023.09.011","type":"journal-article","created":{"date-parts":[[2023,10,18]],"date-time":"2023-10-18T11:42:59Z","timestamp":1697629379000},"page":"241-253","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":48,"title":["Artificial intelligence in osteoarthritis detection: A systematic review and meta-analysis"],"prefix":"10.1016","volume":"32","author":[{"given":"Soheil","family":"Mohammadi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5078-4224","authenticated-orcid":false,"given":"Mohammad Amin","family":"Salehi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6700-6162","authenticated-orcid":false,"given":"Ali","family":"Jahanshahi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad","family":"Shahrabi Farahani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seyed Sina","family":"Zakavi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3742-1266","authenticated-orcid":false,"given":"Sadra","family":"Behrouzieh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mahdi","family":"Gouravani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9374-8266","authenticated-orcid":false,"given":"Ali","family":"Guermazi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.joca.2023.09.011_bib1","doi-asserted-by":"crossref","first-page":"2115","DOI":"10.1016\/S0140-6736(11)60243-2","article-title":"Osteoarthritis: an update with relevance for clinical practice","volume":"377","author":"Bijlsma","year":"2011","journal-title":"Lancet"},{"key":"10.1016\/j.joca.2023.09.011_bib2","doi-asserted-by":"crossref","first-page":"1886","DOI":"10.1007\/s11999-016-4732-4","article-title":"Classifications in brief: Kellgren-Lawrence classification of osteoarthritis","volume":"474","author":"Kohn","year":"2016","journal-title":"Clin Orthop Relat Res"},{"key":"10.1016\/j.joca.2023.09.011_bib3","doi-asserted-by":"crossref","first-page":"246","DOI":"10.15585\/mmwr.mm6609e1","article-title":"Vital signs: prevalence of doctor-diagnosed arthritis and arthritis-attributable activity limitation - United States, 2013-2015","volume":"66","author":"Barbour","year":"2017","journal-title":"MMWR Morb Mortal Wkly Rep"},{"key":"10.1016\/j.joca.2023.09.011_bib4","unstructured":"OARSI. White Paper - OA: a serious disease; 2016."},{"key":"10.1016\/j.joca.2023.09.011_bib5","doi-asserted-by":"crossref","first-page":"1500","DOI":"10.1002\/art.1780381017","article-title":"The incidence and natural history of knee osteoarthritis in the elderly. The Framingham Osteoarthritis Study","volume":"38","author":"Felson","year":"1995","journal-title":"Arthritis Rheum"},{"key":"10.1016\/j.joca.2023.09.011_bib6","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1136\/ard.16.4.494","article-title":"Radiological assessment of osteo-arthrosis","volume":"16","author":"Kellgren","year":"1957","journal-title":"Ann Rheum Dis"},{"key":"10.1016\/j.joca.2023.09.011_bib7","doi-asserted-by":"crossref","first-page":"1233","DOI":"10.1016\/j.joca.2015.03.036","article-title":"Call for standardized definitions of osteoarthritis and risk stratification for clinical trials and clinical use","volume":"23","author":"Kraus","year":"2015","journal-title":"Osteoarthr Cartil"},{"key":"10.1016\/j.joca.2023.09.011_bib8","doi-asserted-by":"crossref","first-page":"1085","DOI":"10.1016\/j.rcl.2017.04.012","article-title":"Imaging in Osteoarthritis","volume":"55","author":"Hayashi","year":"2017","journal-title":"Radiol Clin N Am"},{"key":"10.1016\/j.joca.2023.09.011_bib9","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1001\/jama.2020.22171","article-title":"Diagnosis and treatment of hip and knee osteoarthritis: a review","volume":"325","author":"Katz","year":"2021","journal-title":"JAMA"},{"issue":"9","key":"10.1016\/j.joca.2023.09.011_bib10","doi-asserted-by":"crossref","first-page":"e721","DOI":"10.5435\/JAAOS-D-21-01233","article-title":"AAOS clinical practice guideline summary: management of osteoarthritis of the knee (nonarthroplasty), third edition","volume":"30","author":"Brophy","year":"2022","journal-title":"J Am Acad Orthop Surg"},{"key":"10.1016\/j.joca.2023.09.011_bib11","doi-asserted-by":"crossref","first-page":"2013","DOI":"10.1016\/j.joca.2016.07.017","article-title":"Disease-modifying treatments for osteoarthritis (DMOADs) of the knee and hip: lessons learned from failures and opportunities for the future","volume":"24","author":"Karsdal","year":"2016","journal-title":"Osteoarthr Cartil"},{"key":"10.1016\/j.joca.2023.09.011_bib12","doi-asserted-by":"crossref","first-page":"1848","DOI":"10.1177\/0956797613479386","article-title":"The invisible gorilla strikes again: sustained inattentional blindness in expert observers","volume":"24","author":"Drew","year":"2013","journal-title":"Psychol Sci"},{"key":"10.1016\/j.joca.2023.09.011_bib13","doi-asserted-by":"crossref","first-page":"e25","DOI":"10.3928\/01477447-20121217-14","article-title":"Validity and reliability of radiographic knee osteoarthritis measures by arthroplasty surgeons","volume":"36","author":"Riddle","year":"2013","journal-title":"Orthopedics"},{"key":"10.1016\/j.joca.2023.09.011_bib14","doi-asserted-by":"crossref","DOI":"10.1148\/ryai.2020190065","article-title":"Automated classification of radiographic knee osteoarthritis severity using deep neural networks","volume":"2","author":"Thomas","year":"2020","journal-title":"Radiol Artif Intell"},{"key":"10.1016\/j.joca.2023.09.011_bib15","doi-asserted-by":"crossref","DOI":"10.1016\/j.ocarto.2020.100069","article-title":"Machine learning in knee osteoarthritis: a review","volume":"2","author":"Kokkotis","year":"2020","journal-title":"Osteoarthr Cartil Open"},{"key":"10.1016\/j.joca.2023.09.011_bib16","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-018-20132-7","article-title":"Automatic knee osteoarthritis diagnosis from plain radiographs: a deep learning-based approach","volume":"8","author":"Tiulpin","year":"2018","journal-title":"Sci Rep"},{"key":"10.1016\/j.joca.2023.09.011_bib17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/s21186189","article-title":"A novel hybrid approach based on deep CNN features to detect knee osteoarthritis","volume":"21","author":"Mahum","year":"2021","journal-title":"Sensors"},{"key":"10.1016\/j.joca.2023.09.011_bib18","unstructured":"Macaskill P, Deeks J , Harbord R , Takwoingi Y. GC (2010) Cochrane handbook for systematic reviews of diagnostic test accuracy, 0.9.0. The Cochrane Collaboration."},{"key":"10.1016\/j.joca.2023.09.011_bib19","first-page":"S456880","article-title":"MIDAS: stata module for meta-analytical integration of diagnostic test accuracy studies","volume":"3-9","author":"Dwamena","year":"2007","journal-title":"Stat Softw Components"},{"key":"10.1016\/j.joca.2023.09.011_bib20","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1177\/1536867X0900900203","article-title":"Metandi: meta-analysis of diagnostic accuracy using hierarchical logistic regression","volume":"9","author":"Harbord","year":"2009","journal-title":"Stata J"},{"issue":"1","key":"10.1016\/j.joca.2023.09.011_bib21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12916-014-0241-z","article-title":"Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement","volume":"13","author":"Reitsma","year":"2015","journal-title":"BMC Med"},{"key":"10.1016\/j.joca.2023.09.011_bib22","doi-asserted-by":"crossref","first-page":"51","DOI":"10.7326\/M18-1376","article-title":"PROBAST: a tool to assess the risk of bias and applicability of prediction model studies","volume":"170","author":"Wolff","year":"2019","journal-title":"Ann Intern Med"},{"key":"10.1016\/j.joca.2023.09.011_bib23","doi-asserted-by":"crossref","first-page":"882","DOI":"10.1016\/j.jclinepi.2005.01.016","article-title":"The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed","volume":"58","author":"Deeks","year":"2005","journal-title":"J Clin Epidemiol"},{"issue":"1","key":"10.1016\/j.joca.2023.09.011_bib24","first-page":"12","article-title":"A siamese network with adaptive gated feature fusion for individual knee OA features grades prediction","volume":"11","author":"Wang","year":"2021","journal-title":"Sci Rep"},{"key":"10.1016\/j.joca.2023.09.011_bib25","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1590\/S0102-36162011000200014","article-title":"Computational analysis based on artificial neural networks for aiding in diagnosing osteoarthritis of the lumbar spine","volume":"46","author":"Veronezi","year":"2011","journal-title":"Rev Bras Ortop"},{"key":"10.1016\/j.joca.2023.09.011_bib26","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1007\/s10278-021-00564-w","article-title":"Automated classification of rheumatoid arthritis, osteoarthritis, and normal hand radiographs with deep learning methods","volume":"35","author":"\u00dcreten","year":"2022","journal-title":"J Digit Imaging"},{"key":"10.1016\/j.joca.2023.09.011_bib27","doi-asserted-by":"crossref","first-page":"1369","DOI":"10.1007\/s00256-020-03433-9","article-title":"Detection of hip osteoarthritis by using plain pelvic radiographs with deep learning methods","volume":"49","author":"\u00dcreten","year":"2020","journal-title":"Skelet Radiol"},{"key":"10.1016\/j.joca.2023.09.011_bib28","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2021.104334","article-title":"Deep learning-based algorithm for assessment of knee osteoarthritis severity in radiographs matches performance of radiologists","volume":"133","author":"Swiecicki","year":"2021","journal-title":"Comput Biol Med"},{"key":"10.1016\/j.joca.2023.09.011_bib29","first-page":"4279","article-title":"Automatic detection and classification of human knee osteoarthritis using convolutional neural networks","volume":"70","author":"Sikkandar","year":"2022","journal-title":"Comput Mater Contin"},{"key":"10.1016\/j.joca.2023.09.011_bib30","doi-asserted-by":"crossref","first-page":"2985","DOI":"10.1007\/s11063-021-10529-3","article-title":"Grading of knee osteoarthritis using convolutional neural networks","volume":"53","author":"Sarvamangala","year":"2021","journal-title":"Neural Process Lett"},{"key":"10.1016\/j.joca.2023.09.011_bib31","doi-asserted-by":"crossref","first-page":"1079","DOI":"10.1007\/s11760-020-01645-z","article-title":"X-ray image analysis for automated knee osteoarthritis detection","volume":"14","author":"Saleem","year":"2020","journal-title":"Signal Image Video Process"},{"key":"10.1016\/j.joca.2023.09.011_bib32","first-page":"1549","article-title":"Artificial intelligence assistance in radiographic detection and classification of knee osteoarthritis and its severity: a cross-sectional diagnostic study","volume":"26","author":"Pongsakonpruttikul","year":"2022","journal-title":"Eur Rev Med Pharmacol Sci"},{"key":"10.1016\/j.joca.2023.09.011_bib33","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.1016\/j.joca.2019.02.800","article-title":"Diagnosing osteoarthritis from T2 maps using deep learning: an analysis of the entire Osteoarthritis Initiative baseline cohort","volume":"27","author":"Pedoia","year":"2019","journal-title":"Osteoarthr Cartil"},{"key":"10.1016\/j.joca.2023.09.011_bib34","doi-asserted-by":"crossref","first-page":"957S","DOI":"10.1177\/1947603519888793","article-title":"Automated knee osteoarthritis assessment increases physicians\u2019 agreement rate and accuracy: data from the osteoarthritis initiative","volume":"13","author":"Nehrer","year":"2021","journal-title":"Cartilage"},{"key":"10.1016\/j.joca.2023.09.011_bib35","first-page":"1","article-title":"Dense neural networks in knee osteoarthritis classification: a study on accuracy and fairness","volume":"35","author":"Moustakidis","year":"2020","journal-title":"Neural Comput Appl"},{"key":"10.1016\/j.joca.2023.09.011_bib36","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1007\/s42484-019-00008-3","article-title":"Application of machine intelligence for osteoarthritis classification: a classical implementation and a quantum perspective","volume":"1","author":"Moustakidis","year":"2019","journal-title":"Quantum Mach Intell"},{"key":"10.1016\/j.joca.2023.09.011_bib37","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1007\/s11548-019-02096-9","article-title":"Toward automatic quantification of knee osteoarthritis severity using improved Faster R-CNN","volume":"15","author":"Liu","year":"2020","journal-title":"Int J Comput Assist Radiol Surg"},{"key":"10.1016\/j.joca.2023.09.011_bib38","first-page":"1","article-title":"Expert system for mandibular condyle detection and osteoarthritis classification in panoramic imaging using r-cnn and cnn","volume":"10","author":"Kim","year":"2020","journal-title":"Appl Sci"},{"key":"10.1016\/j.joca.2023.09.011_bib39","first-page":"1","article-title":"Can additional patient information improve the diagnostic performance of deep learning for the interpretation of knee osteoarthritis severity","volume":"9","author":"Kim","year":"2020","journal-title":"J Clin Med"},{"key":"10.1016\/j.joca.2023.09.011_bib40","doi-asserted-by":"crossref","first-page":"39757","DOI":"10.1109\/ACCESS.2021.3062493","article-title":"DeepKneeExplainer: Explainable knee osteoarthritis diagnosis from radiographs and magnetic resonance imaging","volume":"9","author":"Karim","year":"2021","journal-title":"IEEE Access"},{"key":"10.1016\/j.joca.2023.09.011_bib41","doi-asserted-by":"crossref","first-page":"257","DOI":"10.32604\/csse.2022.021606","article-title":"Prediction model using reinforcement deep learning technique for osteoarthritis disease diagnosis","volume":"42","author":"Kanthavel","year":"2022","journal-title":"Comput Syst Sci Eng"},{"issue":"1","key":"10.1016\/j.joca.2023.09.011_bib42","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1038\/s41598-021-81786-4","article-title":"Deep learning for early detection of pathological changes in X-ray bone microstructures: case of osteoarthritis","volume":"11","author":"Jakaite","year":"2021","journal-title":"Sci Rep"},{"key":"10.1016\/j.joca.2023.09.011_bib43","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1007\/s10439-019-02227-y","article-title":"Bone density and texture from minimally post-processed knee radiographs in subjects with knee osteoarthritis","volume":"47","author":"Hirvasniemi","year":"2019","journal-title":"Ann Biomed Eng"},{"key":"10.1016\/j.joca.2023.09.011_bib44","first-page":"1","article-title":"Multicentre study using machine learning methods in clinical diagnosis of knee osteoarthritis","volume":"2021","author":"Zeng","year":"2021","journal-title":"J Healthc Eng"},{"key":"10.1016\/j.joca.2023.09.011_bib45","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/app11115196","article-title":"Knee osteoarthritis classification using 3D CNN and MRI","volume":"11","author":"Guida","year":"2021","journal-title":"Appl Sci"},{"key":"10.1016\/j.joca.2023.09.011_bib46","first-page":"64","article-title":"Identification of region of interest for assessment of knee osteoarthritis in radiographic images","volume":"13","author":"Gornale","year":"2021","journal-title":"Int J Med Eng Inform"},{"key":"10.1016\/j.joca.2023.09.011_bib47","doi-asserted-by":"crossref","first-page":"2429","DOI":"10.35940\/ijitee.L3011.1081219","article-title":"Detection of osteoarthritis in knee radiographic images using artificial neural network","volume":"8","author":"Gornale","year":"2019","journal-title":"Int J Innov Technol Explor Eng"},{"key":"10.1016\/j.joca.2023.09.011_bib48","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1007\/s00198-021-06130-y","article-title":"Detecting hip osteoarthritis on clinical CT: a deep learning application based on 2-D summation images derived from CT","volume":"33","author":"Gebre","year":"2022","journal-title":"Osteoporos Int"},{"issue":"1","key":"10.1016\/j.joca.2023.09.011_bib49","first-page":"7","article-title":"Artificial intelligence in detecting temporomandibular joint osteoarthritis on orthopantomogram","volume":"11","author":"Choi","year":"2021","journal-title":"Sci Rep"},{"key":"10.1016\/j.joca.2023.09.011_bib50","doi-asserted-by":"crossref","DOI":"10.3390\/biology10111107","article-title":"Superiority of multiple-joint space width over minimum-joint space width approach in the machine learning for radiographic severity and knee osteoarthritis progression","volume":"10","author":"Cheung","year":"2021","journal-title":"Biology"},{"key":"10.1016\/j.joca.2023.09.011_bib51","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.compmedimag.2019.06.002","article-title":"Fully automatic knee osteoarthritis severity grading using deep neural networks with a novel ordinal loss","volume":"75","author":"Chen","year":"2019","journal-title":"Comput Med Imaging Graph"},{"key":"10.1016\/j.joca.2023.09.011_bib52","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.compmedimag.2019.01.007","article-title":"A decision support tool for early detection of knee OsteoArthritis using X-ray imaging and machine learning: data from the OsteoArthritis Initiative","volume":"73","author":"Brahim","year":"2019","journal-title":"Comput Med Imaging Graph"},{"key":"10.1016\/j.joca.2023.09.011_bib53","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.1016\/j.nima.2007.06.068","article-title":"A morphological descriptors-based pattern recognition system for the characterization of hip osteoarthritis severity from X-ray images","volume":"580","author":"Boniatis","year":"2007","journal-title":"Nucl Instruments Methods Phys Res Sect A Accel Spectrometers Detect Assoc Equip"},{"key":"10.1016\/j.joca.2023.09.011_bib54","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.medengphy.2006.03.003","article-title":"Assessing hip osteoarthritis severity utilizing a probabilistic neural network based classification scheme","volume":"29","author":"Boniatis","year":"2007","journal-title":"Med Eng Phys"},{"key":"10.1016\/j.joca.2023.09.011_bib55","doi-asserted-by":"crossref","first-page":"41497","DOI":"10.1007\/s11042-021-10557-0","article-title":"Knee osteoarthritis severity classification with ordinal regression module","volume":"81","author":"Yong","year":"2021","journal-title":"Multimed Tools Appl"},{"key":"10.1016\/j.joca.2023.09.011_bib56","first-page":"1112","article-title":"Automated detection for the severity of knee osteoarthritis from plain radiographs using machine learning methods","volume":"8","author":"Bhat","year":"2019","journal-title":"Int J Sci Technol Res"},{"key":"10.1016\/j.joca.2023.09.011_bib57","first-page":"6026","article-title":"Normal and abnormal detection for knee osteoarthritis using machine learning techniques","volume":"8","author":"Bhat","year":"2019","journal-title":"Int J Recent Technol Eng"},{"key":"10.1016\/j.joca.2023.09.011_bib58","doi-asserted-by":"crossref","first-page":"104627","DOI":"10.1016\/j.ijmedinf.2021.104627","article-title":"Machine learning based texture analysis of patella from X-rays for detecting patellofemoral osteoarthritis","volume":"157","author":"Bayramoglu","year":"2022","journal-title":"Int J Med Inform"},{"key":"10.1016\/j.joca.2023.09.011_bib59","doi-asserted-by":"crossref","first-page":"1432","DOI":"10.1016\/j.joca.2021.06.011","article-title":"Automated detection of patellofemoral osteoarthritis from knee lateral view radiographs using deep learning: data from the Multicenter Osteoarthritis Study (MOST)","volume":"29","author":"Bayramoglu","year":"2021","journal-title":"Osteoarthr Cartil"},{"key":"10.1016\/j.joca.2023.09.011_bib60","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-021-93851-z","article-title":"Interpretable and parameter optimized ensemble model for knee osteoarthritis assessment using radiographs","volume":"11","author":"Bany Muhammad","year":"2021","journal-title":"Sci Rep"},{"key":"10.1016\/j.joca.2023.09.011_bib61","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1007\/s11547-022-01476-7","article-title":"Automatic detection and classification of knee osteoarthritis using deep learning approach","volume":"127","author":"Abdullah","year":"2022","journal-title":"Radiol Med"},{"key":"10.1016\/j.joca.2023.09.011_bib62","doi-asserted-by":"crossref","first-page":"110249","DOI":"10.1016\/j.ejrad.2022.110249","article-title":"External validation of an artificial intelligence tool for radiographic knee osteoarthritis severity classification","volume":"150","author":"Brejneb\u00f8l","year":"2022","journal-title":"Eur J Radiol"},{"key":"10.1016\/j.joca.2023.09.011_bib63","doi-asserted-by":"crossref","first-page":"4346","DOI":"10.1109\/TMI.2020.3017007","article-title":"Semixup: in- and out-of-manifold regularization for deep semi-supervised knee osteoarthritis severity grading from plain radiographs","volume":"39","author":"Nguyen","year":"2020","journal-title":"IEEE Trans Med Imaging"},{"issue":"1","key":"10.1016\/j.joca.2023.09.011_bib64","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1186\/s12891-021-04722-7","article-title":"Automating classification of osteoarthritis according to Kellgren-Lawrence in the knee using deep learning in an unfiltered adult population","volume":"22","author":"Olsson","year":"2021","journal-title":"BMC Musculoskelet Disord"},{"key":"10.1016\/j.joca.2023.09.011_bib65","doi-asserted-by":"crossref","first-page":"2423","DOI":"10.1016\/j.arth.2020.04.059","article-title":"Can a convolutional neural network classify knee osteoarthritis on plain radiographs as accurately as fellowship-trained knee arthroplasty surgeons?","volume":"35","author":"Schwartz","year":"2020","journal-title":"J Arthroplast"},{"key":"10.1016\/j.joca.2023.09.011_bib66","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pone.0178992","article-title":"A preliminary examination of the diagnostic value of deep learning in hip osteoarthritis","volume":"12","author":"Xue","year":"2017","journal-title":"PLoS One"},{"key":"10.1016\/j.joca.2023.09.011_bib67","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/diagnostics10110932","article-title":"Automatic grading of individual knee osteoarthritis features in plain radiographs using deep convolutional neural networks","volume":"10","author":"Tiulpin","year":"2020","journal-title":"Diagnostics"},{"key":"10.1016\/j.joca.2023.09.011_bib68","doi-asserted-by":"crossref","first-page":"2968","DOI":"10.3906\/elk-1912-23","article-title":"Detection of hand osteoarthritis from hand radiographs using convolutional neural networks with transfer learning","volume":"28","author":"\u00dcreten","year":"2020","journal-title":"Turk J Electr Eng Comput Sci"},{"key":"10.1016\/j.joca.2023.09.011_bib69","doi-asserted-by":"crossref","first-page":"1787","DOI":"10.19026\/rjaset.8.1166","article-title":"Genetic algorithm optimized back propagation neural network for knee osteoarthritis classification","volume":"8","author":"WeiKoh","year":"2014","journal-title":"Res J Appl Sci Eng Technol"},{"key":"10.1016\/j.joca.2023.09.011_bib70","first-page":"3379","article-title":"Computer-aided diagnosis of early knee osteoarthritis based on MRI T2 mapping","volume":"24","author":"Wu","year":"2014","journal-title":"Biomed Mater Eng"},{"key":"10.1016\/j.joca.2023.09.011_bib71","first-page":"5586529","article-title":"An automatic knee osteoarthritis diagnosis method based on deep learning: data from the osteoarthritis initiative","volume":"2021","author":"Wang","year":"2021","journal-title":"J Healthc Eng"},{"key":"10.1016\/j.joca.2023.09.011_bib72","doi-asserted-by":"crossref","first-page":"1239","DOI":"10.1109\/JBHI.2021.3102090","article-title":"Learning from highly confident samples for automatic knee osteoarthritis severity assessment: data from the Osteoarthritis Initiative","volume":"26","author":"Wang","year":"2022","journal-title":"IEEE J Biomed Health Inform"},{"key":"10.1016\/j.joca.2023.09.011_bib73","doi-asserted-by":"crossref","first-page":"1688","DOI":"10.1109\/TMI.2022.3146973","article-title":"Follow my eye: using gaze to supervise computer-aided diagnosis","volume":"41","author":"Wang","year":"2022","journal-title":"IEEE Trans Med Imaging"},{"key":"10.1016\/j.joca.2023.09.011_bib74","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pone.0258855","article-title":"Towards novel osteoarthritis biomarkers: multi-criteria evaluation of 46,996 segmented knee MRI data from the Osteoarthritis Initiative","volume":"16","author":"Tack","year":"2021","journal-title":"PLoS One"},{"key":"10.1016\/j.joca.2023.09.011_bib75","doi-asserted-by":"crossref","first-page":"859","DOI":"10.1016\/j.joca.2021.02.561","article-title":"Machine learning classi fi cation on texture analyzed T2 maps of osteoarthritic cartilage: oulu knee osteoarthritis study Osteoarthritis","volume":"29","author":"Peuna","year":"2021","journal-title":"Osteoarthr Cartil"},{"key":"10.1016\/j.joca.2023.09.011_bib76","first-page":"561","article-title":"Computer-aided knee osteoarthritis classification system using Artificial Neural Netwrok (ANN)","volume":"3","author":"En","year":"2013","journal-title":"J Med Imaging Health Inform"},{"key":"10.1016\/j.joca.2023.09.011_bib77","doi-asserted-by":"crossref","first-page":"8513","DOI":"10.1007\/s00330-021-07951-5","article-title":"A machine learning approach to distinguish between knees without and with osteoarthritis using MRI-based radiomic features from tibial bone","volume":"31","author":"Hirvasniemi","year":"2021","journal-title":"Eur Radiol"},{"key":"10.1016\/j.joca.2023.09.011_bib78","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1002\/mrm.24477","article-title":"Diagnosis of osteoarthritis and prognosis of tibial cartilage loss by quantification of tibia trabecular bone from MRI","volume":"70","author":"Marques","year":"2013","journal-title":"Magn Reson Med"},{"key":"10.1016\/j.joca.2023.09.011_bib79","doi-asserted-by":"crossref","first-page":"2190","DOI":"10.1002\/mrm.28251","article-title":"Learning osteoarthritis imaging biomarkers from bone surface spherical encoding","volume":"84","author":"Morales Martinez","year":"2020","journal-title":"Magn Reson Med"},{"key":"10.1016\/j.joca.2023.09.011_bib80","doi-asserted-by":"crossref","first-page":"1363","DOI":"10.1177\/0022034520936950","article-title":"Automated detection of TMJ osteoarthritis based on artificial intelligence","volume":"99","author":"Lee","year":"2020","journal-title":"J Dent Res"},{"key":"10.1016\/j.joca.2023.09.011_bib81","first-page":"1","article-title":"Deep learning for osteoarthritis classification in temporomandibular joint","volume":"29","author":"Jung","year":"2021","journal-title":"Oral Dis"},{"key":"10.1016\/j.joca.2023.09.011_bib82","first-page":"203","article-title":"Measures of diagnostic accuracy: basic definitions","volume":"19","author":"\u0160imundi\u0107","year":"2009","journal-title":"EJIFCC"},{"key":"10.1016\/j.joca.2023.09.011_bib83","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.eclinm.2020.100669","article-title":"Artificial intelligence performance in detecting tumor metastasis from medical radiology imaging: A systematic review and meta-analysis","volume":"31","author":"Zheng","year":"2021","journal-title":"EClinicalMedicine"},{"key":"10.1016\/j.joca.2023.09.011_bib84","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1148\/radiol.211785","article-title":"Artificial intelligence in fracture detection: a systematic review and meta-analysis","volume":"304","author":"Kuo","year":"2022","journal-title":"Radiology"}],"container-title":["Osteoarthritis and Cartilage"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1063458423009482?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1063458423009482?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T04:00:52Z","timestamp":1761019252000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1063458423009482"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3]]},"references-count":84,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2024,3]]}},"alternative-id":["S1063458423009482"],"URL":"https:\/\/doi.org\/10.1016\/j.joca.2023.09.011","relation":{},"ISSN":["1063-4584"],"issn-type":[{"value":"1063-4584","type":"print"}],"subject":[],"published":{"date-parts":[[2024,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Artificial intelligence in osteoarthritis detection: A systematic review and meta-analysis","name":"articletitle","label":"Article Title"},{"value":"Osteoarthritis and Cartilage","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.joca.2023.09.011","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2023 Osteoarthritis Research Society International. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}]}}