Enhancing Diagnostic Precision in Dyslexia : Introducing the DYSLEX Platform

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14210%2F24%3A00139824" target="_blank" >RIV/00216224:14210/24:00139824 - isvavai.cz</a>

Result on the web

<a href="https://65wa.icet2024.org/" target="_blank" >https://65wa.icet2024.org/</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Enhancing Diagnostic Precision in Dyslexia : Introducing the DYSLEX Platform

Original language description

The presentation, explores an innovative approach to diagnosing dyslexia using eye-tracking technology and artificial intelligence. Utilizing eye-tracking devices and AI algorithms, the research differentiates between dyslexic and non-dyslexic readers, offering a more objective and precise diagnostic method. The findings demonstrate that deep learning models, such as multilayer perceptrons and residual neural networks, can achieve approximately 90% accuracy in classifying dyslexia. The study underscores the potential of AI in transforming traditional diagnostic processes and highlights future steps towards digitizing dyslexia diagnosis in collaboration with psychological counseling centers.

Czech name

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Czech description

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Type

O - Miscellaneous

CEP classification

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OECD FORD branch

50301 - Education, general; including training, pedagogy, didactics [and education systems]

Project

<a href="/en/project/TL05000177" target="_blank" >TL05000177: Diagnostics of dyslexia using eye-tracking and artificial intelligence</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů