Artificial intelligence support improves diagnosis accuracy in anterior segment eye diseases.

ABSTRACT: CorneAI, a deep learning model designed for diagnosing cataracts and corneal diseases, was assessed for its impact on ophthalmologists' diagnostic accuracy. In the study, 40 ophthalmologists (20 specialists and 20 residents) classified 100 images, including iPhone 13 Pro photos (50 images) and diffuser slit-lamp photos (50 images), into nine categories (normal condition, infectious keratitis, immunological keratitis, corneal scar, corneal deposit, bullous keratopathy, ocular surface tumor, cataract/intraocular lens opacity, and primary angle-closure glaucoma). The iPhone and slit-lamp images represented the same cases. After initially answering without CorneAI, the same ophthalmologists responded to the same cases with CorneAI 2-4 weeks later. With CorneAI's support, the overall accuracy o

SUBMITTER: Maehara H 

PROVIDER: S-EPMC11814138 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature