Open AccessMachine learning algorithms for prediction of dyslexia using eye movement
Author(s) -
Vani Chakraborty,
Meentachi Sundaram
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1427/1/012012
Subject(s) - dyslexia , spelling , worry , learning disability , psychology , cognitive psychology , movement (music) , eye movement , computer science , developmental psychology , artificial intelligence , reading (process) , linguistics , anxiety , philosophy , psychiatry , aesthetics
Dyslexia is the most widely recognized neurological learning disability. It causes trouble in perusing, composing and spelling. All these can influence scholastic achievement, confidence, and social-emotional development. As roughly 10% of the individuals worldwide are dyslexic, it is a worry of numerous youngsters and grown-ups far and wide. Figuring out how to help the lives of a dyslexic would be of incredible advantage to entire social orders. Studies have demonstrated that the earlier dyslexia is recognized and backing is given in education and training, the more its negative impacts can be alleviated. Subsequently, building up a solid and target screening technique to analyze dyslexia at an early age would be of most extreme significance.