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

Mustapha Jaouhari¹, Chaimae El Harrak¹, Farida Bentayeb²

¹Laboratory of Electronic, Mechanical, and Energetic Information Processing Systems, Faculty of Sciences, Ibn Tofail University, Morocco.

The British and Irish Orthoptic Journal

|March 2, 2026

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A new web-based tool accurately identifies children at high risk for amblyopia using AI and parent-reported factors. This screening method is effective for resource-limited settings, ensuring early detection of visual impairment.

Area of Science:

Ophthalmology
Artificial Intelligence
Pediatric Health

Background:

Amblyopia is the leading cause of childhood visual impairment.
Limited access to eye care specialists hinders early detection in many regions.
Effective screening tools are crucial for timely intervention.

Purpose of the Study:

To assess the accuracy of a novel web-based screening tool for identifying children at risk of amblyopia.
The tool integrates parent-reported risk factors and AI-driven strabismus detection.
To evaluate the tool's potential in resource-limited settings.

Main Methods:

A pilot study involved 105 children (aged 3-10) in Morocco.
Parents completed an online questionnaire on amblyopia risk factors.

Keywords:

Amblyopia screening Artificial intelligence Paediatric vision Preventive eye care School screening Strabismus detection Web-based tool

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AI analyzed smartphone photos for strabismus, using CNNs and geometric measurements.

Children were categorized into high, moderate, or low-risk groups based on a total score.

Main Results:

The tool achieved 100% positive predictive value (PPV) for high-risk children, all confirmed with amblyopia.
No low-risk children were diagnosed with amblyopia (100% negative predictive value).
The AI strabismus module showed 96.9% accuracy in the high-risk group.

Conclusions:

The hybrid screening tool reliably identifies high-risk children for amblyopia, aligning with clinical diagnoses.
It effectively excludes low-risk children, demonstrating safety.
This accessible, low-cost approach is promising for pediatric vision screening in underserved areas.
Further large-scale studies are needed to confirm generalizability.