Evaluating Artificial Intelligence as a First-Pass Reader in Fundus Photograph Screening: A Multireader Workflow Validation Study

Background/Objectives: Double reading with arbitration improves diagnostic reliability in fundus screening but requires repeated human interpretation. Whether artificial intelligence (AI) can serve as a first-pass decision source within this workflow, and whether this applies consistently across retinal diseases with differing inter-reader agreement, remains unclear. Methods: In this retrospective study, 6904 color fundus photographs from 2593 patients at a tertiary screening center were analyzed for age-related macular degeneration (AMD), diabetic retinopathy (DR), and retinal vein occlusion (RVO). Three retina specialists independently labeled each image, and an AI system provided binary classifications at a prespecified operating threshold targeting 0.99-sensitivity. In AI–human double reading, the AI and one reader independently interpreted each image, and a second reader arbitrated discordant cases; this was compared with conventional human–human double reading. Three reader combinations were evaluated per disease. Results: AI–human reading required 1.02–1.11 human reads per image versus 2.00–2.10 for human–human reading. For DR and RVO, human–human reading yielded sensitivities of 0.974 and 0.982 and specificities of 0.999 and 1.000, respectively. Across AI–human combinations, sensitivity and specificity did not differ significantly from human–human reading (all p ≥ 0.05; specificity differences ≤0.001). For AMD (human–human sensitivity 0.845, specificity 1.000), AI–human sensitivity varied: two combinations were higher (0.916 and 0.950; both p < 0.001) and one comparable (0.842; p = 0.742). AMD specificity remained ≥0.978. Conclusions: AI–human reading halved human reading volume without significant loss for DR and RVO; AMD varied by configuration. AI use within double-reading workflows should account for disease-specific inter-reader agreement, reader composition, and operating threshold. This was a single-center, retrospective study, prospective external validation in a multicenter setting is warranted before clinical implementation.