Pilot Evaluation of a Web Application for Amblyopia Risk Screening Integrating Parent-Reported Factors with AI-Assisted Strabismus Detection

Abstract

Background: Amblyopia is the most common cause of visual impairment in children, and early detection is essential, yet screening remains limited in many settings, especially where access to eye-care specialists is scarce. Objective: To evaluate the accuracy of a web-based screening tool that combines parent-reported risk factors with AI-assisted strabismus detection for identifying children at risk of amblyopia. Methods: This pilot study included 105 children aged 3-10 years attending a public hospital in Morocco for their first ophthalmological evaluation. Parents completed an online screening tool consisting of eight validated amblyopia risk-factor questions and an automated strabismus analysis based on a frontal smartphone photograph. The AI module combined geometric measurements of pupil-nasal root symmetry with convolutional neural network (CNN) features such as corneal light reflex and gaze vector orientation. Each child received a total score (0-9), stratified into high-risk (6-9), moderate-risk (3-6), or low-risk (0-3) categories. A comprehensive ophthalmological examination, performed by a clinician blinded to the application results, served as the reference standard. Results: Of the 105 children screened, 32 were classified as high-risk, 62 as moderate-risk, and 11 as low-risk. The tool demonstrated perfect agreement in the high-risk category, with all 32 high-risk children clinically confirmed to have amblyopia (PPV = 100%). In the moderate-risk group, 30 of the 62 children were clinically confirmed (PPV = 48.4%). No child in the low-risk group had amblyopia (NPV = 100%). The AI-assisted strabismus module showed strong predictive accuracy in the high-risk category (96.9% confirmation). Statistical analyses showed no significant differences in diagnostic performance across age, gender, or urban/rural subgroups (p > 0.05). Conclusions: The hybrid screening tool reliably identified children at high risk for amblyopia with complete concordance with a blinded clinical diagnosis, while safely excluding low-risk children. Although moderate-risk scores require cautious interpretation and clinical follow-up, this approach offers a low-cost, accessible, and scalable solution for paediatric vision screenings in resource-limited settings. Further large-scale community-based studies are warranted to validate generalisability.