ArticleEye (London, England)2024
An artificial intelligence platform for the screening and managing of strabismus.
Article in Eye (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Stakeholder experience with artificial intelligence in healthcare: a bibliometric study of satisfaction, trust, acceptance, and patient engagement.Frontiers in digital health · 2026Pooled it
- Systematic review and meta-analysis of artificial intelligence models for strabismus screening: methodological insights and future directions.International journal of surgery (London, England) · 2025Pooled it
- Clinical research on the application of AI-assisted computing systems in the treatment of intermittent exotropia.BMC ophthalmology · 2025Trial
- Design and clinical evaluation of a virtual reality-based system for automated ocular deviation measurement.Medical & biological engineering & computing · 2026Article
- Accuracy and Effectiveness of AI-Powered Systems in Patient Counseling, Education, and Management in Optometry and Related Eye-Care Settings: A Systematic Review.Healthcare (Basel, Switzerland) · 2026Review
- Sustainable Ophthalmology Applications: From the Perspective of Strabismus and Pediatric Ophthalmology.Turkish journal of ophthalmology · 2026Review
- Quantitative Assessment of Strabismus Using Cloud AI Computing: Validation Study.JMIR formative research · 2025Article
- Article
- Deep Learning-Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization.Journal of medical Internet research · 2025Article
- High-Accuracy Intermittent Strabismus Screening via Wearable Eye-Tracking and AI-Enhanced Ocular Feature Analysis.Biosensors · 2025Article
- Integrated visual and text-based analysis of ophthalmology clinical cases using a large language model.Scientific reports · 2025Article
- Automated strabismus detection and classification using deep learning analysis of facial images.Scientific reports · 2025Article
- Integrating artificial intelligence in strabismus management: current research landscape and future directions.Experimental biology and medicine (Maywood, N.J.) · 2024Review
Corrections and comments
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Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesConsidering the escalating incidence of strabismus and its consequential jeopardy to binocular vision, there is an imperative demand for expeditious and precise screening methods. This study was to develop an artificial intelligence (AI) platform in the form of an applet that facilitates the screening and management of strabismus on any mobile device.
methodsThe Visual Transformer (VIT_16_224) was developed using primary gaze photos from two datasets covering different ages. The AI model was evaluated by 5-fold cross-validation set and tested on an independent test set. The diagnostic performance of the AI model was assessed by calculating the Accuracy, Precision, Specificity, Sensitivity, F1-Score and Area Under the Curve (AUC).
resultsA total of 6194 photos with corneal light-reflection (with 2938 Exotropia, 1415 Esotropia, 739 Vertical Deviation and 1562 Orthotropy) were included. In the internal validation set, the AI model achieved an Accuracy of 0.980, Precision of 0.941, Specificity of 0.979, Sensitivity of 0.958, F1-Score of 0.951 and AUC of 0.994. In the independent test set, the AI model achieved an Accuracy of 0.967, Precision of 0.980, Specificity of 0.970, Sensitivity of 0.960, F1-Score of 0.975 and AUC of 0.993.
conclusionsOur study presents an advanced AI model for strabismus screening which integrates electronic archives for comprehensive patient histories. Additionally, it includes a patient-physician interaction module for streamlined communication. This innovative platform offers a complete solution for strabismus care, from screening to long-term follow-up, advancing ophthalmology through AI technology for improved patient outcomes and eye care quality.
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Registered trials
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.