Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus · 2026
Offline AI-assisted fundus imaging for preliminary screening of childhood glaucoma.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Senthil Sirisha, Rao Divya Parthasarathy, Bhandary Shreya, Krishnamurthy Rashmi, Negiloni Kalpa
Аннотация
PURPOSE: To evaluate the feasibility and performance of AI-assisted portable fundus photography in children with glaucoma.
METHODS: This case series describes the use of smartphone-based fundus imaging with integrated offline glaucoma artificial intelligence (AI) in children (≤18 years) with various types of glaucoma who were evaluated at a tertiary eye care center, and comparing AI-derived referral recommendations with presence or absence of structural optic nerve changes determined on clinical evaluation.
RESULTS: AI-assisted fundus photography and clinical evaluation were completed for 21 children. For vertical cup:disk ratio, the 95% limits of agreement between AI image analysis and clinical assessment on Bland-Altman analysis were -0.15 to +0.23. The AI output recommended referral for 7 of 8 children who had structural optic nerve changes on clinical examination and did not recommend referral for any of the children without such optic nerve changes.
CONCLUSIONS: AI-assisted smartphone-based fundus imaging may help identify cases of pediatric glaucoma exhibiting structural optic nerve changes.
METHODS: This case series describes the use of smartphone-based fundus imaging with integrated offline glaucoma artificial intelligence (AI) in children (≤18 years) with various types of glaucoma who were evaluated at a tertiary eye care center, and comparing AI-derived referral recommendations with presence or absence of structural optic nerve changes determined on clinical evaluation.
RESULTS: AI-assisted fundus photography and clinical evaluation were completed for 21 children. For vertical cup:disk ratio, the 95% limits of agreement between AI image analysis and clinical assessment on Bland-Altman analysis were -0.15 to +0.23. The AI output recommended referral for 7 of 8 children who had structural optic nerve changes on clinical examination and did not recommend referral for any of the children without such optic nerve changes.
CONCLUSIONS: AI-assisted smartphone-based fundus imaging may help identify cases of pediatric glaucoma exhibiting structural optic nerve changes.