{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T12:28:24Z","timestamp":1793536104478,"version":"4.5.0"},"reference-count":35,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T00:00:00Z","timestamp":1788480000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["canadianjournalofophthalmology.ca","clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Canadian Journal of Ophthalmology"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.jcjo.2026.08.036","type":"journal-article","created":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T12:03:08Z","timestamp":1793534588000},"update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep learning retinal vein occlusion diagnosis: a systematic review and meta-analysis"],"prefix":"10.1016","author":[{"given":"Fahad R.","family":"Butt","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1548-1519","authenticated-orcid":false,"given":"Kyran","family":"Sachdeva","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0571-2894","authenticated-orcid":false,"given":"Thanansayan","family":"Dhivagaran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmed Eltom","family":"Mohamed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4044-3215","authenticated-orcid":false,"given":"Salem Abu","family":"Al-Burak","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7069-3162","authenticated-orcid":false,"given":"Brendan K.","family":"Tao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Mihalache","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3404-5376","authenticated-orcid":false,"given":"Ryan S.","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rajeev H.","family":"Muni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0370-5968","authenticated-orcid":false,"given":"Marko M.","family":"Popovic","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.jcjo.2026.08.036_bib0001","doi-asserted-by":"crossref","DOI":"10.7189\/jogh.09.010427","article-title":"Global epidemiology of retinal vein occlusion: a systematic review and meta\u2013analysis of prevalence, incidence, and risk factors","volume":"9","author":"Song","year":"2019","journal-title":"J Glob Health"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0002","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1136\/bjophthalmol-2021-319030","article-title":"Accuracy of automated machine learning in classifying retinal pathologies from ultra\u2013widefield pseudocolour fundus images","volume":"107","author":"Antaki","year":"2023","journal-title":"Br J Ophthalmol"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0003","doi-asserted-by":"crossref","first-page":"1895","DOI":"10.18240\/ijo.2021.12.13","article-title":"Artificial intelligence can assist with diagnosing retinal vein occlusion","volume":"14","author":"Chen","year":"2021","journal-title":"Int J Ophthalmol"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0004","doi-asserted-by":"crossref","DOI":"10.1155\/2022\/1730501","article-title":"Hypermixed convolutional neural network for retinal vein occlusion classification","volume":"2022","author":"Zhang","year":"2022","journal-title":"Dis Markers"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0005","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.csda.2014.09.021","article-title":"Performance measures of the bivariate random effects model for meta-analyses of diagnostic accuracy","volume":"83","author":"Diaz","year":"2015","journal-title":"Comput Stat Data Anal"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0006","doi-asserted-by":"crossref","first-page":"304","DOI":"10.2337\/dc23-0993","article-title":"Performance of artificial intelligence in detecting diabetic macular edema from fundus photography and optical coherence tomography images: a systematic review and meta-analysis","volume":"47","author":"Lam","year":"2024","journal-title":"Diabetes Care"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0007","doi-asserted-by":"crossref","first-page":"277","DOI":"10.3904\/kjim.2016.195","article-title":"An overview of meta-analysis for clinicians","volume":"33","author":"Lee","year":"2018","journal-title":"Korean J Intern Med"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0008","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1002\/mp.16012","article-title":"Assessing retinal vein occlusion based on color fundus photographs using neural understanding network (NUN)","volume":"50","author":"Beeche","year":"2023","journal-title":"Med Phys"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0009","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1186\/s12938-023-01097-9","article-title":"Application effect of an artificial intelligence\u2013based fundus screening system: evaluation in a clinical setting and population screening","volume":"22","author":"Cao","year":"2023","journal-title":"Biomed Eng Online"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0010","doi-asserted-by":"crossref","first-page":"4828","DOI":"10.1038\/s41467-021-25138-w","article-title":"Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks","volume":"12","author":"Cen","year":"2021","journal-title":"Nat Commun"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0011","article-title":"Automated interpretation of retinal vein occlusion based on fundus fluorescein angiography images using deep learning: a retrospective, multi-center study","volume":"10","author":"Huang","year":"2024","journal-title":"Heliyon"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0012","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18240\/ijo.2024.01.01","article-title":"Intelligent diagnosis of retinal vein occlusion based on color fundus photographs","volume":"17","author":"Ji","year":"2024","journal-title":"Int J Ophthalmol"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0013","doi-asserted-by":"crossref","DOI":"10.2196\/28868","article-title":"A multimodal imaging\u2013based deep learning model for detecting treatment\u2013requiring retinal vascular diseases: model development and validation study","volume":"9","author":"Kang","year":"2021","journal-title":"JMIR Med Inform"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0014","doi-asserted-by":"crossref","first-page":"189","DOI":"10.3390\/diagnostics13020189","article-title":"The classification of common macular diseases using deep learning on optical coherence tomography images with and without prior automated segmentation","volume":"13","author":"Kaothanthong","year":"2023","journal-title":"Diagnostics (Basel)"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0015","doi-asserted-by":"crossref","first-page":"321","DOI":"10.3390\/jpm11050321","article-title":"Development of a fundus image\u2013based deep learning diagnostic tool for various retinal diseases","volume":"11","author":"Kim","year":"2021","journal-title":"J Pers Med"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0016","doi-asserted-by":"crossref","first-page":"e486","DOI":"10.1016\/S2589-7500(21)00086-8","article-title":"Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study","volume":"3","author":"Lin","year":"2021","journal-title":"Lancet Digit Health"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0017","doi-asserted-by":"crossref","first-page":"2067","DOI":"10.1109\/TMI.2022.3155154","article-title":"Weakly-supervised learning with complementary heatmap for retinal disease detection","volume":"41","author":"Meng","year":"2022","journal-title":"IEEE Trans Med Imaging"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0018","doi-asserted-by":"crossref","DOI":"10.1155\/2018\/1875431","article-title":"Deep neural network\u2013based method for detecting central retinal vein occlusion using ultrawide\u2013field fundus ophthalmoscopy","volume":"2018","author":"Nagasato","year":"2018","journal-title":"J Ophthalmol"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0019","first-page":"94","article-title":"Deep-learning classifier with ultrawide-field fundus ophthalmoscopy for detecting branch retinal vein occlusion","volume":"12","author":"Nagasato","year":"2019","journal-title":"Int J Ophthalmol"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0020","doi-asserted-by":"crossref","first-page":"5619","DOI":"10.1038\/s41598-020-62329-9","article-title":"Automated quantification of photoreceptor alteration in macular disease using optical coherence tomography and deep learning","volume":"10","author":"Orlando","year":"2020","journal-title":"Sci Rep"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0021","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1167\/tvst.13.12.31","article-title":"A deep learning network for accurate retinal multidisease diagnosis using multiview fusion of en face and B-scan images: a multicenter study","volume":"13","author":"Ou","year":"2024","journal-title":"Transl Vis Sci Technol"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0022","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1167\/tvst.11.9.29","article-title":"Etiology of macular edema defined by deep learning in optical coherence tomography scans","volume":"11","author":"Padilla-Pantoja","year":"2022","journal-title":"Transl Vis Sci Technol"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0023","doi-asserted-by":"crossref","DOI":"10.1088\/2057-1976\/ad27ea","article-title":"RD-OCT net: hybrid learning system for automated diagnosis of macular diseases from OCT retinal images","volume":"10","author":"Prabha","year":"2024","journal-title":"Biomed Phys Eng Express"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0024","doi-asserted-by":"crossref","first-page":"2026","DOI":"10.1038\/s41433-022-02239-4","article-title":"Artificial intelligence to distinguish retinal vein occlusion patients using color fundus photographs","volume":"37","author":"Ren","year":"2023","journal-title":"Eye"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0025","doi-asserted-by":"crossref","first-page":"895","DOI":"10.1007\/s40123-022-00627-3","article-title":"Deep learning for the detection of multiple fundus diseases using ultra-widefield Images","volume":"12","author":"Sun","year":"2023","journal-title":"Ophthalmol Ther"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0026","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1007\/s00417-023-06182-2","article-title":"An auxiliary diagnostic tool for common fundus diseases based on fundus color photography and light-weight classification models","volume":"262","author":"Wang","year":"2024","journal-title":"Graefes Arch Clin Exp Ophthalmol"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0027","doi-asserted-by":"crossref","first-page":"6757","DOI":"10.1038\/s41467-023-42444-7","article-title":"Uncertainty-inspired open set learning for retinal anomaly identification","volume":"14","author":"Wang","year":"2023","journal-title":"Nat Commun"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0028","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2023.107148","article-title":"DeepDrRVO: a GAN-auxiliary two\u2013step masked transformer framework benefits early recognition and differential diagnosis of retinal vascular occlusion from color fundus photographs","volume":"163","author":"Yang","year":"2023","journal-title":"Comput Biol Med"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0029","article-title":"An artificial intelligence system for the whole process from diagnosis to treatment suggestion of ischemic retinal diseases","volume":"4","author":"Zhao","year":"2023","journal-title":"Cell Rep Med"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0030","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1167\/tvst.10.7.20","article-title":"Five-category intelligent auxiliary diagnosis model of common fundus diseases based on fundus images","volume":"10","author":"Zheng","year":"2021","journal-title":"Transl Vis Sci Technol"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0031","doi-asserted-by":"crossref","DOI":"10.1155\/2022\/4988256","article-title":"Development and application of an intelligent diagnosis system for retinal vein occlusion based on deep learning","volume":"2022","author":"Xu","year":"2022","journal-title":"Dis Markers"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0032","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1186\/s40942-025-00670-9","article-title":"The efficacy of artificial intelligence in diabetic retinopathy screening: a systematic review and meta-analysis","volume":"11","author":"Alqahtani","year":"2025","journal-title":"Int J Retina Vitreous"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0033","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1016\/j.ajo.2025.05.041","article-title":"Performance of artificial intelligence\u2013based models for epiretinal membrane diagnosis: a systematic review and meta-analysis","volume":"277","author":"Mikhail","year":"2025","journal-title":"Am J Ophthalmol"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0034","article-title":"A comprehensive review of deep learning in OCT image segmentation and classification","volume":"28","author":"Abdi","year":"2025","journal-title":"Med Novel Technol Dev"},{"key":"10.1016\/j.jcjo.2026.08.036_bib0035","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.survophthal.2025.07.003","article-title":"Multimodal artificial intelligence in ophthalmology: applications, challenges, and future directions","volume":"71","author":"Jin","year":"2026","journal-title":"Surv Ophthalmol"}],"container-title":["Canadian Journal of Ophthalmology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0008418226003583?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0008418226003583?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T12:03:12Z","timestamp":1793534592000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0008418226003583"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":35,"alternative-id":["S0008418226003583"],"URL":"https:\/\/doi.org\/10.1016\/j.jcjo.2026.08.036","relation":{},"ISSN":["0008-4182"],"issn-type":[{"value":"0008-4182","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Deep learning retinal vein occlusion diagnosis: a systematic review and meta-analysis","name":"articletitle","label":"Article Title"},{"value":"Canadian Journal of Ophthalmology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jcjo.2026.08.036","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Inc. on behalf of Canadian Ophthalmological Society.","name":"copyright","label":"Copyright"}]}}