{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T16:09:50Z","timestamp":1792858190214,"version":"4.5.0"},"reference-count":17,"publisher":"BMJ","content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["Br J Ophthalmol"],"accepted":{"date-parts":[[2026,6,14]]},"abstract":"<jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>To evaluate a real-world clinical integration of an autonomous artificial intelligence (AI) system (AEYE Diagnostic Screening (AEYE-DS), AEYE Health, USA) for diabetic retinopathy (DR) screening using the Topcon NW500 camera (Topcon, Japan) in an endocrinology clinic.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Adults with type 1 or type 2 diabetes without previously reported DR attending routine endocrinology follow-up were invited to participate. Non-mydriatic, macula-centred fundus photographs were acquired by a novice, non-ophthalmic operator. Images were analysed by AEYE-DS to detect more-than-mild DR (mtmDR). AI-positive results prompted physician counselling and automated referral for internal confirmatory examination.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Definitive AEYE-DS results were obtained for 95.7% (245\/256) of participants without pharmacological dilation. Seventy-six (29.6%) patients screened positive for mtmDR, of whom 34 (44.7%) completed confirmatory examination at the institution\u2019s retina clinic; externally completed follow-up was not captured. Four patients (11.8% of those evaluated) required treatment with intravitreal anti-vascular endothelial growth factor therapy or panretinal photocoagulation. Additional previously unrecognised ocular conditions were identified among several AI-positive patients. Patient satisfaction was high, with &gt;80% reporting the screening was easy to use, time-efficient and recommendable.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>In a real-world endocrinology clinic, autonomous AI screening for DR using AEYE-DS integrated with the Topcon NW500 enabled efficient DR screening and achieved high non-mydriatic imageability. A clinically relevant proportion of patients requiring ophthalmic evaluation has been captured. Internal referral for confirmatory testing enabled assessment of downstream outcomes. The findings support scalable, point-of-care autonomous screening and a stepped-referral approach for AI-positive patients.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bjo-2025-328991","type":"journal-article","created":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T17:20:21Z","timestamp":1782753621000},"page":"bjo-2025-328991","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":2,"title":["Real-world integration of an autonomous artificial intelligence system for diabetic retinopathy screening in an endocrinology outpatient clinic"],"prefix":"10.1136","author":[{"given":"Or","family":"Gil","sequence":"first","affiliation":[{"name":"The Goldschleger Eye Institute, Gray Faculty of Medical & Health Sciences, Tel-Aviv University, Chaim Sheba Medical Center, Tel Aviv-Yafo, Tel Aviv District, 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