[HTML][HTML] Technologies to support the diagnosis and/or treatment of neurodevelopmental disorders: A systematic review

MO Ribas, M Micai, A Caruso, F Fulceri, M Fazio… - Neuroscience & …, 2023 - Elsevier
In recent years, there has been a great interest in utilizing technology in mental health
research. The rapid technological development has encouraged researchers to apply …

[HTML][HTML] EEG-based functional connectivity analysis of brain abnormalities: A review study

N Khaleghi, S Hashemi, M Peivandi, SZ Ardabili… - Informatics in Medicine …, 2024 - Elsevier
Several imaging modalities and many signal recording techniques have been used to study
the brain activities. Significant advancements in medical device technologies like …

ADHD detection using dynamic connectivity patterns of EEG data and ConvLSTM with attention framework

M Bakhtyari, S Mirzaei - Biomedical Signal Processing and Control, 2022 - Elsevier
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental behavioral disorder.
It is common in children, can be carried over into adulthood, and is associated with …

[HTML][HTML] A comparison of resting state EEG and structural MRI for classifying Alzheimer's disease and mild cognitive impairment

FR Farina, DD Emek-Savaş, L Rueda-Delgado… - Neuroimage, 2020 - Elsevier
Alzheimer's disease (AD) is the leading cause of dementia, accounting for 70% of cases
worldwide. By 2050, dementia prevalence will have tripled, with most new cases occurring …

Automatic identification of children with ADHD from EEG brain waves

A Alim, MH Imtiaz - Signals, 2023 - mdpi.com
EEG (electroencephalogram) signals could be used reliably to extract critical information
regarding ADHD (attention deficit hyperactivity disorder), a childhood neurodevelopmental …

EEG biomarkers related with the functional state of stroke patients

M Sebastián-Romagosa, E Udina, R Ortner… - Frontiers in …, 2020 - frontiersin.org
Introduction Recent studies explored promising new quantitative methods to analyze
electroencephalography (EEG) signals. This paper analyzes the correlation of two EEG …

Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry

Z Chen, B Hu, X Liu, B Becker, SB Eickhoff, K Miao… - BMC medicine, 2023 - Springer
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 …

Direction of information flow between brain regions in ADHD and healthy children based on EEG by using directed phase transfer entropy

A Ekhlasi, AM Nasrabadi, MR Mohammadi - Cognitive Neurodynamics, 2021 - Springer
Directed information flow between brain regions might be disrupted in children with Attention
Deficit Hyperactivity Disorder (ADHD) which is related to the behavioral characteristics of …

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 …

Classification of the children with ADHD and healthy children based on the directed phase transfer entropy of EEG signals

A Ekhlasi, AM Nasrabadi… - Frontiers in …, 2021 - publish.kne-publishing.com
Purpose: The present study was conducted to investigate and classify two groups of healthy
children and children with Attention Deficit Hyperactivity Disorder (ADHD) by Effective …