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Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project

INTRODUCTION: Around 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...

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Autores principales: Pueyo, Victoria, Pérez-Roche, Teresa, Prieto, Esther, Castillo, Olimpia, Gonzalez, Inmaculada, Alejandre, Adrian, Pan, Xian, Fanlo-Zarazaga, Alvaro, Pinilla, Juan, Echevarria, Jose Ignacio, Gutierrez, Diego, Altemir, Irene, Romero-Sanz, María, Cipres, Marta, Ortin, Marta, Masia, Belen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7044912/
https://www.ncbi.nlm.nih.gov/pubmed/32071178
http://dx.doi.org/10.1136/bmjopen-2019-033139
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author Pueyo, Victoria
Pérez-Roche, Teresa
Prieto, Esther
Castillo, Olimpia
Gonzalez, Inmaculada
Alejandre, Adrian
Pan, Xian
Fanlo-Zarazaga, Alvaro
Pinilla, Juan
Echevarria, Jose Ignacio
Gutierrez, Diego
Altemir, Irene
Romero-Sanz, María
Cipres, Marta
Ortin, Marta
Masia, Belen
author_facet Pueyo, Victoria
Pérez-Roche, Teresa
Prieto, Esther
Castillo, Olimpia
Gonzalez, Inmaculada
Alejandre, Adrian
Pan, Xian
Fanlo-Zarazaga, Alvaro
Pinilla, Juan
Echevarria, Jose Ignacio
Gutierrez, Diego
Altemir, Irene
Romero-Sanz, María
Cipres, Marta
Ortin, Marta
Masia, Belen
author_sort Pueyo, Victoria
collection PubMed
description INTRODUCTION: Around 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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spelling pubmed-70449122020-03-09 Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project Pueyo, Victoria Pérez-Roche, Teresa Prieto, Esther Castillo, Olimpia Gonzalez, Inmaculada Alejandre, Adrian Pan, Xian Fanlo-Zarazaga, Alvaro Pinilla, Juan Echevarria, Jose Ignacio Gutierrez, Diego Altemir, Irene Romero-Sanz, María Cipres, Marta Ortin, Marta Masia, Belen BMJ Open Ophthalmology INTRODUCTION: Around 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. BMJ Publishing Group 2020-02-17 /pmc/articles/PMC7044912/ /pubmed/32071178 http://dx.doi.org/10.1136/bmjopen-2019-033139 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Ophthalmology
Pueyo, Victoria
Pérez-Roche, Teresa
Prieto, Esther
Castillo, Olimpia
Gonzalez, Inmaculada
Alejandre, Adrian
Pan, Xian
Fanlo-Zarazaga, Alvaro
Pinilla, Juan
Echevarria, Jose Ignacio
Gutierrez, Diego
Altemir, Irene
Romero-Sanz, María
Cipres, Marta
Ortin, Marta
Masia, Belen
Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project
title Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project
title_full Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project
title_fullStr Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project
title_full_unstemmed Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project
title_short Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project
title_sort development of a system based on artificial intelligence to identify visual problems in children: study protocol of the trackai project
topic Ophthalmology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7044912/
https://www.ncbi.nlm.nih.gov/pubmed/32071178
http://dx.doi.org/10.1136/bmjopen-2019-033139
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