Advance machine learning methods for dyslexia biomarker detection: A review of implementation details and challenges

OL Usman, RC Muniyandi, K Omar, M Mohamad - IEEE Access, 2021 - ieeexplore.ieee.org
Dyslexia is a neurological disorder that is characterized by imprecise comprehension of
words and generally poor reading performance. It affects a significant population of school …

A systematic review of research dimensions towards dyslexia screening using machine learning

TG Jan, SM Khan - Journal of The Institution of Engineers (India): Series B, 2023 - Springer
Dyslexia is the hidden learning disability, neurobiological in origin wherein students face
hard time in accurate or fluent word recognition, connecting letters to the sounds. In India …

[HTML][HTML] Deep learning applications for dyslexia prediction

ND Alqahtani, B Alzahrani, MS Ramzan - Applied Sciences, 2023 - mdpi.com
Dyslexia is a neurological problem that leads to obstacles and difficulties in the learning
process, especially in reading. Generally, people with dyslexia suffer from weak reading …

[HTML][HTML] Detection of developmental dyslexia with machine learning using eye movement data

P Raatikainen, J Hautala, O Loberg, T Kärkkäinen… - Array, 2021 - Elsevier
Dyslexia is a common neurocognitive learning disorder that can seriously hinder individuals'
aspirations if not detected and treated early. Instead of costly diagnostic assessment made …

[HTML][HTML] Developmental dyslexia detection using machine learning techniques: A survey

S Kaisar - ICT Express, 2020 - Elsevier
Developmental dyslexia is a learning disability that occurs mostly in children during their
early childhood. Dyslexic children face difficulties while reading, spelling and writing words …

A comprehensive review of machine learning approaches for dyslexia diagnosis

N Ahire, RN Awale, S Patnaik, A Wagh - Multimedia Tools and …, 2023 - Springer
Electroencephalography (EEG) is the commonly employed electro-biological imaging
technique for diagnosing brain functioning. The EEG signals are used to determine head …

[HTML][HTML] Eye tracking based dyslexia detection using a holistic approach

B Nerušil, J Polec, J Škunda, J Kačur - Scientific Reports, 2021 - nature.com
A new detection method for cognitive impairments is presented utilizing an eye tracking
signals in a text reading test. This research enhances published articles that extract …

[HTML][HTML] Integrating oversampling and ensemble-based machine learning techniques for an imbalanced dataset in dyslexia screening tests

S Kaisar, A Chowdhury - ICT Express, 2022 - Elsevier
Developmental Dyslexia is a learning disorder often discovered in school-aged children
who face difficulties while reading or spelling words even though they may have average or …

[HTML][HTML] Dyslexia detection using 3D convolutional neural networks and functional magnetic resonance imaging

S Zahia, B Garcia-Zapirain, I Saralegui… - Computer methods and …, 2020 - Elsevier
Abstract Background and Objectives: Dyslexia is a disorder of neurological origin which
affects the learning of those who suffer from it, mainly children, and causes difficulty in …

EEG connectivity analysis using denoising autoencoders for the detection of dyslexia

FJ Martinez-Murcia, A Ortiz, JM Gorriz… - … Journal of Neural …, 2020 - World Scientific
The Temporal Sampling Framework (TSF) theorizes that the characteristic phonological
difficulties of dyslexia are caused by an atypical oscillatory sampling at one or more …