Efficient diagnostic classification of diverse pathologies through contextual eye movement data analysis with a novel hybrid architecture
Author:
Funder
Orasis-Ear & ANRT, CIFRE
Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41598-024-68056-9.pdf
Reference91 articles.
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2. El Hmimdi, A. E., Ward, L. M., Palpanas, T., Garnot, S. F. & Kapoula, V. Z. Predicting dyslexia in adolescents from eye movements during free painting viewing. Brain Sci. 12, 1031 (2022).
3. Jothi Prabha, A. & Bhargavi, R. Prediction of dyslexia from eye movements using machine learning. IETE J. Res. 68, 814–823 (2022).
4. Nerušil, B., Polec, J., Škunda, J. & Kačur, J. Eye tracking based dyslexia detection using a holistic approach. Sci. Rep. 11, 15687 (2021).
5. Nilsson Benfatto, M. et al. Screening for dyslexia using eye tracking during reading. PLoS ONE 11, e0165508 (2016).
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