Enhancing Diagnostic Precision in Dyslexia : Introducing the DYSLEX Platform

Kód výsledku v 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>

Výsledek na webu

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

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Enhancing Diagnostic Precision in Dyslexia : Introducing the DYSLEX Platform

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Enhancing Diagnostic Precision in Dyslexia : Introducing the DYSLEX Platform

Popis výsledku anglicky

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.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

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

Projekt

<a href="/cs/project/TL05000177" target="_blank" >TL05000177: Diagnostika dyslexie s využitím eye-trackingu a umělé inteligence</a><br>

Návaznosti

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

Rok uplatnění

2024

Kód důvěrnosti údajů

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