Evidence map›Paper›PMID 41768363›Full record

ArticleThe British and Irish orthoptic journal2026

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

Mustapha Jaouhari, Chaimae El Harrak, Farida Bentayeb, Youssef Elmerabet

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Article in The British and Irish orthoptic journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mustapha JaouhariLaboratory of Electronic, Mechanical, and Energetic Information Processing Systems, Faculty of Sciences, Ibn Tofail University, Morocco.ORCID https://orcid.org/0009-0006-0819-5182
Chaimae El HarrakLaboratory of Electronic, Mechanical, and Energetic Information Processing Systems, Faculty of Sciences, Ibn Tofail University, Morocco.ORCID https://orcid.org/0009-0008-4632-8622
Farida BentayebLaboratory of Engineering and Materials (LIMAT), Hassan II University of Casablanca, Faculty of Sciences Ben M'Sick, Morocco.ORCID https://orcid.org/0000-0003-2773-8016
Youssef ElmerabetLaboratory of Electronic, Mechanical, and Energetic Information Processing Systems, Faculty of Sciences, Ibn Tofail University, Morocco.ORCID https://orcid.org/0000-0001-6938-9374

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Amblyopia screeningArtificial intelligencePaediatric visionPreventive eye careSchool screeningStrabismus detectionWeb-based tool

Identifiers

PMID41768363
PMCPMC12947816

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.