ArticleScience advances2019
Autonomous early detection of eye disease in childhood photographs.
Article in Science advances, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Effectiveness of smartphone technology for detection of paediatric ocular diseases-a systematic review.BMC ophthalmology · 2025Pooled it
- Home-based screening tools for amblyopia: a systematic review.Eye (London, England) · 2023Pooled it
- Detection of pediatric cataracts through non-invasive facial photography using deep convolutional neural networks for early diagnosis.BMC ophthalmology · 2026Observational
- Smartphone applications for early screening of retinoblastoma: a scoping review.BMC ophthalmology · 2026Article
- Machine learning demonstrates clinical utility in distinguishing retinoblastoma from pseudo retinoblastoma with RetCam images.Ophthalmic genetics · 2025Article
- Deep learning-based mobile application for efficient eyelid tumor recognition in clinical images.NPJ digital medicine · 2025Article
- Global health inequities in retinoblastoma: a 1990-2021 analysis across socio-demographic index regions.Frontiers in public health · 2025Article
- RDLR: A Robust Deep Learning-Based Image Registration Method for Pediatric Retinal Images.Journal of imaging informatics in medicine · 2024Article
- Clinical Applications of Machine Learning in the Management of Intraocular Cancers: A Narrative Review.Investigative ophthalmology & visual science · 2023Review
- Early detection of visual impairment in young children using a smartphone-based deep learning system.Nature medicine · 2023Article
- Detection and Diagnosis of Retinoblastoma: Can Mobile Devices Be the Next Step Toward Early Intervention?Cureus · 2022Review
- Evaluation of the red reflex: An overview for the pediatrician.World journal of methodology · 2021Article
- [Telemedical applications in ophthalmology in times of COVID-19].Der Ophthalmologe : Zeitschrift der Deutschen Ophthalmologischen Gesellschaft · 2021Review
- Effectiveness of Kanna photoscreener in detecting amblyopia risk factors.Indian journal of ophthalmology · 2021Article
- Etiology of white pupillary reflex in pediatric age group.Romanian journal of ophthalmologyArticle
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The "red reflex test" is used to screen children for leukocoria ("white eye") in a standard pediatric examination, but is ineffective at detecting many eye disorders. Leukocoria also presents in casual photographs. The clinical utility of screening photographs for leukocoria is unreported. Here, a free smartphone application (CRADLE: ComputeR-Assisted Detector of LEukocoria) was engineered to detect photographic leukocoria and is available for download under the name "White Eye Detector." This study determined the sensitivity, specificity, and accuracy of CRADLE by retrospectively analyzing 52,982 longitudinal photographs of children, collected by parents before enrollment in this study. The cohort included 20 children with retinoblastoma, Coats' disease, cataract, amblyopia, or hyperopia and 20 control children. For 80% of children with eye disorders, the application detected leukocoria in photographs taken before diagnosis by 1.3 years (95% confidence interval, 0.4 to 2.3 years). The CRADLE application allows parents to augment clinical leukocoria screening with photography.
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Registered trials
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