Enhancing Diagnostic Precision in Dyslexia: Introducing the DYSLEX Platform
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| Year of publication | 2024 |
| Type | Appeared in Conference without Proceedings |
| MU Faculty or unit | |
| Citation | |
| 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. |
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