{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T21:31:05Z","timestamp":1792099865589,"version":"4.4.0"},"reference-count":61,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"5","license":[{"start":{"date-parts":[[2023,5,1]],"date-time":"2023-05-01T00:00:00Z","timestamp":1682899200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0"}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,5]]},"abstract":"<jats:p>Diabetic macular edema (DME) is an important cause of visual impairment in the working-age group. Deep learning methods have been developed to detect DME from two-dimensional retinal images and also from optical coherence tomography (OCT) images. The performances of these algorithms vary and often create doubt regarding their clinical utility. In resource-constrained health-care systems, these algorithms may play an important role in determining referral and treatment. The survey provides a diversified overview of macular edema detection methods, including cutting-edge research, with the objective of providing pertinent information to research groups, health-care professionals, and diabetic patients about the applications of deep learning in retinal image detection and classification process. Electronic databases such as PubMed, IEEE Explore, BioMed, and Google Scholar were searched from inception to March 31, 2022, and the reference lists of published papers were also searched. The study followed the preferred reporting items for systematic review and meta-analysis (PRISMA) reporting guidelines. Examination of various deep learning models and their exhibition regarding precision, epochs, their capacity to detect anomalies for less training data, concepts, and challenges that go deep into the applications were analyzed. A total of 53 studies were included that evaluated the performance of deep learning models in a total of 1,414,169\u00b0CT volumes, B-scans, patients, and 472,328 fundus images. The overall area under the receiver operating characteristic curve (AUROC) was 0.9727. The overall sensitivity for detecting DME using OCT images was 96% (95% confidence interval [CI]: 0.94\u20130.98). The overall sensitivity for detecting DME using fundus images was 94% (95% CI: 0.90\u20130.96).<\/jats:p>","DOI":"10.4103\/ijo.ijo_2614_22","type":"journal-article","created":{"date-parts":[[2023,5,17]],"date-time":"2023-05-17T03:38:03Z","timestamp":1684294683000},"page":"1783-1796","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":32,"title":["Deep learning\u2013based detection of diabetic macular edema using optical coherence tomography and fundus images: A meta-analysis"],"prefix":"10.4103","volume":"71","author":[{"given":"Suchetha","family":"Manikandan","sequence":"first","affiliation":[{"name":"Professor & Deputy Director, Centre for Healthcare Advancement, Innovation & Research, Vellore Institute of Technology, Chennai, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rajiv","family":"Raman","sequence":"additional","affiliation":[{"name":"Senior Consultant, Shri Bhagwan Mahavir Vitreoretinal Services, Sankara Nethralaya, Chennai, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramachandran","family":"Rajalakshmi","sequence":"additional","affiliation":[{"name":"Head Medical Retina, Dr. Mohan\u2019s Diabetes Specialties Centre and Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S","family":"Tamilselvi","sequence":"additional","affiliation":[{"name":"Junior Research Fellow, Centre for Healthcare Advancement, Innovation & Research,Vellore Institute of Technology, Chennai, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R Janani","family":"Surya","sequence":"additional","affiliation":[{"name":"Research Associate, Vision Research Foundation, Chennai, Tamil Nadu, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2023,5,17]]},"reference":[{"key":"R1-20251006","doi-asserted-by":"crossref","first-page":"76","DOI":"10.4103\/0301-4738.178145","article-title":"Advances in retinal imaging for diabetic retinopathy and diabetic macular edema","volume":"64","author":"Tan","year":"2016","journal-title":"Indian J Ophthalmol"},{"key":"R2-20251006","doi-asserted-by":"crossref","first-page":"2968","DOI":"10.4103\/ijo.IJO_1212_21","article-title":"Current status and future possibilities of retinal imaging in diabetic retinopathy care applicable to low- and medium-income countries","volume":"69","author":"Attiku","year":"2021","journal-title":"Indian J Ophthalmol"},{"key":"R3-20251006","doi-asserted-by":"crossref","first-page":"1140","DOI":"10.4103\/ijo.IJO_1840_21","article-title":"Acceptability of artificial intelligence-based retina screening in general population","volume":"70","author":"Shah","year":"2022","journal-title":"Indian J Ophthalmol"},{"key":"R4-20251006","doi-asserted-by":"crossref","first-page":"556","DOI":"10.2337\/dc11-1909","article-title":"Global prevalence and major risk factors of diabetic retinopathy","volume":"35","author":"Yau","year":"2012","journal-title":"Diabetes Care"},{"key":"R5-20251006","doi-asserted-by":"crossref","first-page":"671","DOI":"10.4103\/ijo.IJO_2614_20","article-title":"Impact of treatment of diabetic macular edema on visual impairment in people with diabetes mellitus in India","volume":"69","author":"Kulkarni","year":"2021","journal-title":"Indian J Ophthalmol"},{"key":"R6-20251006","doi-asserted-by":"crossref","first-page":"676","DOI":"10.4103\/ijo.IJO_3787_20","article-title":"Commentary:Impact of treatment of diabetic macular edema on visual impairment in people with diabetes mellitus in India","volume":"69","author":"Mishra","year":"2021","journal-title":"Indian J Ophthalmol"},{"key":"R7-20251006","doi-asserted-by":"crossref","first-page":"50","DOI":"10.4103\/0301-4738.178152","article-title":"Diabetic care initiatives to prevent blindness from diabetic retinopathy in India","volume":"64","author":"Murthy","year":"2016","journal-title":"Indian J Ophthalmol"},{"key":"R8-20251006","first-page":"1097","article-title":"ImageNet classi\ufb01cation with deep convolutional neural networks","author":"Krizhevsky","year":"2012","journal-title":"Proc. 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