{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T16:11:30Z","timestamp":1785255090191,"version":"3.55.0"},"reference-count":43,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Clin Med Insights Endocrinol Diabetes"],"published-print":{"date-parts":[[2023,1]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Artificial intelligence (AI) appears capable of detecting diabetic retinopathy (DR) with a high degree of accuracy in adults; however, there are few studies in children and young adults.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>Children and young adults (3-26\u2009years) with type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM) were screened at the Dhaka BIRDEM-2 hospital, Bangladesh. All gradable fundus images were uploaded to Cybersight AI for interpretation. Two main outcomes were considered at a patient level: 1) Any DR, defined as mild non-proliferative diabetic retinopathy (NPDR or more severe; and 2) Referable DR, defined as moderate NPDR or more severe. Diagnostic test performance comparing Orbis International\u2019s Cybersight AI with the reference standard, a fully qualified optometrist certified in DR grading, was assessed using the Matthews correlation coefficient (MCC), area under the receiver operating characteristic curve (AUC-ROC), area under the precision-recall curve (AUC-PR), sensitivity, specificity, positive and negative predictive values.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Among 1274 participants (53.1% female, mean age 16.7\u2009years), 19.4% (n\u2009=\u2009247) had any DR according to AI. For referable DR, 2.35% (n\u2009=\u200930) were detected by AI. The sensitivity and specificity of AI for any DR were 75.5% (CI 69.7-81.3%) and 91.8% (CI 90.2-93.5%) respectively, and for referable DR, these values were 84.2% (CI 67.8-100%) and 98.9% (CI 98.3%-99.5%). The MCC, AUC-ROC and the AUC-PR for referable DR were 63.4, 91.2 and 76.2% respectively. AI was most successful in accurately classifying younger children with shorter duration of diabetes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>Cybersight AI accurately detected any DR and referable DR among children and young adults, despite its algorithms having been trained on adults. The observed high specificity is particularly important to avoid over-referral in low-resource settings. AI may be an effective tool to reduce demands on scarce physician resources for the care of children with diabetes in low-resource settings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/11795514231203867","type":"journal-article","created":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T03:46:54Z","timestamp":1696823214000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":4,"title":["CHILDSTAR: CHIldren Living With Diabetes See and Thrive with AI Review"],"prefix":"10.1177","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7071-109X","authenticated-orcid":false,"given":"Katie","family":"Curran","sequence":"first","affiliation":[{"name":"Centre for Public Health, Queens University Belfast, Belfast, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Noelle","family":"Whitestone","sequence":"additional","affiliation":[{"name":"Orbis International, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bedowra","family":"Zabeen","sequence":"additional","affiliation":[{"name":"Department of Paediatrics, Life for a Child & Changing Diabetes in Children Programme, Bangladesh Institute of Research & Rehabilitation in Diabetes, Endocrine & Metabolic Disorders (BIRDEM), Diabetic Association of Bangladesh, Dhaka, Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Munir","family":"Ahmed","sequence":"additional","affiliation":[{"name":"Orbis Bangladesh, Dhaka, Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lutful","family":"Husain","sequence":"additional","affiliation":[{"name":"Orbis Bangladesh, Dhaka, Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammed","family":"Alauddin","sequence":"additional","affiliation":[{"name":"Orbis Bangladesh, Dhaka, Bangladesh"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad Awlad","family":"Hossain","sequence":"additional","affiliation":[{"name":"Orbis International, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer L","family":"Patnaik","sequence":"additional","affiliation":[{"name":"Orbis International, New York, NY, USA"},{"name":"Department of Ophthalmology, University of Colorado School of Medicine, Aurora, CO, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gabriella","family":"Lanouette","sequence":"additional","affiliation":[{"name":"Orbis International, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David Hunter","family":"Cherwek","sequence":"additional","affiliation":[{"name":"Orbis International, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nathan","family":"Congdon","sequence":"additional","affiliation":[{"name":"Centre for Public Health, Queens University Belfast, Belfast, UK"},{"name":"Orbis International, New York, NY, USA"},{"name":"Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tunde","family":"Peto","sequence":"additional","affiliation":[{"name":"Centre for Public Health, Queens University Belfast, Belfast, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicolas","family":"Jaccard","sequence":"additional","affiliation":[{"name":"Orbis International, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2023,10,9]]},"reference":[{"key":"bibr1-11795514231203867","unstructured":"International Diabetes Federation. 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