ArticleBMJ open2020
Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project.
Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 18 citations in OpenAlex.
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- Validation of a New Digital and Automated Color Perception Test.Diagnostics (Basel, Switzerland) · 2024Article
- Artificial intelligence-based screening for amblyopia and its risk factors: comparison with four classic stereovision tests.Frontiers in medicine · 2023Article
- Visual Acuity and Contrast Sensitivity in Preterm and Full-Term Children Using a Novel Digital Test.Children (Basel, Switzerland) · 2022Article
- Development of oculomotor control throughout childhood: A multicenter and multiethnic study.Journal of vision · 2022Article
- Distributed Intelligent Learning and Decision Model Based on Logic Predictive Control.Computational intelligence and neuroscience · 2022Article
- Recent Advances in Screening and Treatment for Amblyopia.Ophthalmology and therapy · 2021Review
- The Red Reflex Test - Shadow conceals, light reveals.Indian journal of ophthalmology · 2021Article
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Authors and funding
16 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionAround 70% to 80% of the 19 million visually disabled children in the world are due to a preventable or curable disease, if detected early enough. Vision screening in childhood is an evidence-based and cost-effective way to detect visual disorders. However, current screening programmes face several limitations: training required to perform them efficiently, lack of accurate screening tools and poor collaboration from young children.Some of these limitations can be overcome by new digital tools. Implementing a system based on artificial intelligence systems avoid the challenge of interpreting visual outcomes.The objective of the TrackAI Project is to develop a system to identify children with visual disorders. The system will have two main components: a novel visual test implemented in a digital device, DIVE (Device for an Integral Visual Examination); and artificial intelligence algorithms that will run on a smartphone to analyse automatically the visual data gathered by DIVE. METHODS AND ANALYSIS: This is a multicentre study, with at least five centres located in five geographically diverse study sites participating in the recruitment, covering Europe, USA and Asia.The study will include children aged between 6 months and 14 years, both with normal or abnormal visual development.The project will be divided in two consecutive phases: design and training of an artificial intelligence (AI) algorithm to identify visual problems, and system development and validation. The study protocol will consist of a comprehensive ophthalmological examination, performed by an experienced paediatric ophthalmologist, and an exam of the visual function using a DIVE.For the first part of the study, diagnostic labels will be given to each DIVE exam to train the neural network. For the validation, diagnosis provided by ophthalmologists will be compared with AI system outcomes. ETHICS AND DISSEMINATION: The study will be conducted in accordance with the principles of Good Clinical Practice. This protocol was approved by the Clinical Research Ethics Committee of Aragón, CEICA, on January 2019 (Code PI18/346).Results will be published in peer-reviewed journals and disseminated in scientific meetings. TRIAL REGISTRATION NUMBER: ISRCTN17316993.
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