Neuroanatomy of developmental dyslexia: Pitfalls and promise
Investigations into the neuroanatomical bases of developmental dyslexia have now
spanned more than 40 years, starting with the post-mortem examination of a few individual …
spanned more than 40 years, starting with the post-mortem examination of a few individual …
Advance machine learning methods for dyslexia biomarker detection: A review of implementation details and challenges
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 …
words and generally poor reading performance. It affects a significant population of school …
Evaluation of risk of bias in neuroimaging-based artificial intelligence models for psychiatric diagnosis: a systematic review
Z Chen, X Liu, Q Yang, YJ Wang, K Miao… - JAMA network …, 2023 - jamanetwork.com
Importance Neuroimaging-based artificial intelligence (AI) diagnostic models have
proliferated in psychiatry. However, their clinical applicability and reporting quality (ie …
proliferated in psychiatry. However, their clinical applicability and reporting quality (ie …
Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry
Background The development of machine learning models for aiding in the diagnosis of
mental disorder is recognized as a significant breakthrough in the field of psychiatry …
mental disorder is recognized as a significant breakthrough in the field of psychiatry …
A comprehensive review of machine learning approaches for dyslexia diagnosis
Electroencephalography (EEG) is the commonly employed electro-biological imaging
technique for diagnosing brain functioning. The EEG signals are used to determine head …
technique for diagnosing brain functioning. The EEG signals are used to determine head …
Classification of EEG signals from young adults with dyslexia combining a Brain Computer Interface device and an Interactive Linguistic Software Tool
The magnocellular pathway deficit theory has long been considered to be a possible cause
for dyslexia, providing an alternative method to explain auditory and visual processing …
for dyslexia, providing an alternative method to explain auditory and visual processing …
[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 …
who face difficulties while reading or spelling words even though they may have average or …
[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 …
early childhood. Dyslexic children face difficulties while reading, spelling and writing words …
Brain structure, phenotypic and genetic correlates of reading performance
A Carrión-Castillo, PM Paz-Alonso… - Nature Human …, 2023 - nature.com
Reading is an evolutionarily recent development that recruits and tunes brain circuitry
connecting primary-and language-processing regions. We investigated whether metrics of …
connecting primary-and language-processing regions. We investigated whether metrics of …
Prediction of dyslexia severity levels from fixation and saccadic eye movement using machine learning
A JothiPrabha, R Bhargavi, BVD Rani - Biomedical Signal Processing and …, 2023 - Elsevier
Background Dyslexia is a neurological disorder that causes poor reading and
comprehension skills. Dyslexics experience problems in understanding phonemes of …
comprehension skills. Dyslexics experience problems in understanding phonemes of …