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of 6
pro vyhledávání: '"Alae Eddine El Hmimdi"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract The analysis of eye movements has proven valuable for understanding brain function and the neuropathology of various disorders. This research aims to utilize eye movement data analysis as a screening tool for differentiation between eight di
Externí odkaz:
https://doaj.org/article/a699a70b9020443e8caca3e8884f6383
Publikováno v:
BioMedInformatics, Vol 4, Iss 3, Pp 1902-1933 (2024)
Self-supervised learning (SSL) has gained significant attention in the past decade for its capacity to utilize non-annotated datasets to learn meaningful data representations. In the medical domain, the challenge of constructing large annotated datas
Externí odkaz:
https://doaj.org/article/30857142e2314034a78b88d2d788569b
Autor:
Alae Eddine El Hmimdi, Zoï Kapoula
Publikováno v:
BioMedInformatics, Vol 4, Iss 2, Pp 1457-1479 (2024)
In this study, the challenges posed by limited annotated medical data in the field of eye movement AI analysis are addressed through the introduction of a novel physiologically based gaze data augmentation library. Unlike traditional augmentation met
Externí odkaz:
https://doaj.org/article/5209948ec3c0409a81b3c404c15d0aba
Deep Learning-Based Detection of Learning Disorders on a Large Scale Dataset of Eye Movement Records
Publikováno v:
BioMedInformatics, Vol 4, Iss 1, Pp 519-541 (2024)
Early detection of dyslexia and learning disorders is vital for avoiding a learning disability, as well as supporting dyslexic students by tailoring academic programs to their needs. Several studies have investigated using supervised algorithms to sc
Externí odkaz:
https://doaj.org/article/c891da458db446b794a889f39e20b65e
Autor:
Alae Eddine El Hmimdi, Lindsey M Ward, Themis Palpanas, Vivien Sainte Fare Garnot, Zoï Kapoula
Publikováno v:
Brain Sciences, Vol 12, Iss 8, p 1031 (2022)
It is known that dyslexics present eye movement abnormalities. Previously, we have shown that eye movement abnormalities during reading or during saccade and vergence testing can predict dyslexia successfully. The current study further examines this
Externí odkaz:
https://doaj.org/article/7e9c0f1d48394cd39ead400e06fd9b66
Publikováno v:
Brain Sciences, Vol 11, Iss 10, p 1337 (2021)
There is evidence that abnormalities in eye movements exist during reading in dyslexic individuals. A few recent studies applied Machine Learning (ML) classifiers to such eye movement data to predict dyslexia. A general problem with these studies is
Externí odkaz:
https://doaj.org/article/4c2d61d2dc5447ccbe5703fd1f3e13aa