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 …

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 …

Decoding color visual working memory from EEG signals using graph convolutional neural networks

X Che, Y Zheng, X Chen, S Song, S Li - International Journal of …, 2022 - World Scientific
Color has an important role in object recognition and visual working memory (VWM).
Decoding color VWM in the human brain is helpful to understand the mechanism of visual …

Association between decreased interhemispheric functional connectivity of the insula and duration of illness in recurrent depression

ZP Guo, L Chen, LR Tang, Y Gao, T Chand… - Journal of Affective …, 2023 - Elsevier
Objective To investigate the altered interhemispheric functional connectivity in the resting
state in patients with recurrent major depressive disorder (MDD). Methods Voxel-mirrored …

Identifying major depressive disorder based on cerebral blood flow and brain structure: An explainable multimodal learning study

J Hu, Y Hou, B Peng, B Liao, Z Xu, G Hou… - Journal of Psychiatric …, 2025 - Elsevier
Magnetic resonance imaging (MRI) offers non-invasive assessments of brain structure and
function for analyzing brain disorders. With the increasing accumulation of multimodal MRI …

Volumetric assessment of individual thalamic nuclei in patients with drug-naïve, first-episode major depressive disorder

E Chibaatar, K Watanabe, N Okamoto… - Frontiers in …, 2023 - frontiersin.org
Introduction Despite the previous inconsistent findings of structural and functional
abnormalities of the thalamus in patients with major depressive disorder (MDD), the …

[HTML][HTML] Altered effective connectivity from cerebellum to motor cortex in chronic low back pain: A multivariate pattern analysis and spectral dynamic causal modeling …

Y Chen, Y Yang, Z Gong, Y Kang, Y Zhang… - Brain Research …, 2023 - Elsevier
To explore the central processing mechanism of pain perception in chronic low back pain
(cLBP) using multi-voxel pattern analysis (MVPA) based on the static and dynamic fractional …

Aberrant concordance among dynamics of spontaneous brain activity in patients with migraine without aura: A multivariate pattern analysis study

Y Chen, J Xu, J Wu, H Chen, Y Kang, Y Yang, Z Gong… - Heliyon, 2024 - cell.com
Background Alterations in the static and dynamic characteristics of spontaneous brain
activity have been extensively studied to investigate functional brain changes in migraine …

Treatment Response Prediction for Major Depressive Disorder Patients via Multivariate Pattern Analysis of Thalamic Features

H Li, S Song, D Wang, D Zhang, Z Tan… - Frontiers in …, 2022 - frontiersin.org
Antidepressant treatment, as an important method in clinical practice, is not suitable for all
major depressive disorder (MDD) patients. Although magnetic resonance imaging (MRI) …