Neuroimaging in functional neurological disorder: state of the field and research agenda

DL Perez, TR Nicholson, AA Asadi-Pooya, I Bègue… - NeuroImage: Clinical, 2021 - Elsevier
Functional neurological (conversion) disorder (FND) was of great interest to early clinical
neuroscience leaders. During the 20th century, neurology and psychiatry grew apart-leaving …

[HTML][HTML] Artificial intelligence for brain diseases: A systematic review

A Segato, A Marzullo, F Calimeri, E De Momi - APL bioengineering, 2020 - pubs.aip.org
Artificial intelligence (AI) is a major branch of computer science that is fruitfully used for
analyzing complex medical data and extracting meaningful relationships in datasets, for …

MVS-GCN: A prior brain structure learning-guided multi-view graph convolution network for autism spectrum disorder diagnosis

G Wen, P Cao, H Bao, W Yang, T Zheng… - Computers in biology and …, 2022 - Elsevier
Purpose Recently, functional brain networks (FBN) have been used for the classification of
neurological disorders, such as Autism Spectrum Disorders (ASD). Neurological disorder …

Hi-GCN: A hierarchical graph convolution network for graph embedding learning of brain network and brain disorders prediction

H Jiang, P Cao, MY Xu, J Yang, O Zaiane - Computers in Biology and …, 2020 - Elsevier
Purpose Recently, brain connectivity networks have been used for the classification of
neurological disorder, such as Autism Spectrum Disorders (ASD) or Alzheimer's disease …

[HTML][HTML] One size does not fit all: methodological considerations for brain-based predictive modeling in psychiatry

E Dhamala, BTT Yeo, AJ Holmes - Biological Psychiatry, 2023 - Elsevier
Psychiatric illnesses are heterogeneous in nature. No illness manifests in the same way
across individuals, and no two patients with a shared diagnosis exhibit identical symptom …

Functional magnetic resonance imaging in migraine: a systematic review

S Schramm, C Börner, M Reichert, T Baum… - …, 2023 - journals.sagepub.com
Background Migraine is a highly prevalent primary headache disorder. Despite a high
burden of disease, key disease mechanisms are not entirely understood. Functional …

Deep learning for brain disorder diagnosis based on fMRI images

W Yin, L Li, FX Wu - Neurocomputing, 2022 - Elsevier
In modern neuroscience and clinical study, neuroscientists and clinicians often use non-
invasive imaging techniques to validate theories and computational models, observe brain …

Diagnosis of autism spectrum disorder based on functional brain networks with deep learning

W Yin, S Mostafa, FX Wu - Journal of Computational Biology, 2021 - liebertpub.com
Autism spectrum disorder (ASD) is a neurological and developmental disorder. Traditional
diagnosis of ASD is typically performed through the observation of behaviors and interview …

Multi-scale dynamic graph learning for brain disorder detection with functional MRI

Y Ma, Q Wang, L Cao, L Li, C Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Resting-state functional magnetic resonance imaging (rs-fMRI) has been widely used in the
detection of brain disorders such as autism spectrum disorder based on various …

Automatic diagnosis of schizophrenia and attention deficit hyperactivity disorder in rs-fMRI modality using convolutional autoencoder model and interval type-2 fuzzy …

A Shoeibi, N Ghassemi, M Khodatars, P Moridian… - Cognitive …, 2023 - Springer
Nowadays, many people worldwide suffer from brain disorders, and their health is in danger.
So far, numerous methods have been proposed for the diagnosis of Schizophrenia (SZ) and …