An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future …

D Sadeghi, A Shoeibi, N Ghassemi, P Moridian… - Computers in Biology …, 2022 - Elsevier
Schizophrenia (SZ) is a mental disorder that typically emerges in late adolescence or early
adulthood. It reduces the life expectancy of patients by 15 years. Abnormal behavior …

Classification and prediction of brain disorders using functional connectivity: promising but challenging

Y Du, Z Fu, VD Calhoun - Frontiers in neuroscience, 2018 - frontiersin.org
Brain functional imaging data, especially functional magnetic resonance imaging (fMRI)
data, have been employed to reflect functional integration of the brain. Alteration in brain …

Evidence for embracing normative modeling

S Rutherford, P Barkema, IF Tso, C Sripada… - Elife, 2023 - elifesciences.org
In this work, we expand the normative model repository introduced in Rutherford et al.,
2022a to include normative models charting lifespan trajectories of structural surface area …

Towards a brain‐based predictome of mental illness

B Rashid, V Calhoun - Human brain mapping, 2020 - Wiley Online Library
Neuroimaging‐based approaches have been extensively applied to study mental illness in
recent years and have deepened our understanding of both cognitively healthy and …

Dynamics of large-scale electrophysiological networks: A technical review

GC O'Neill, P Tewarie, D Vidaurre, L Liuzzi… - NeuroImage, 2018 - Elsevier
For several years it has been argued that neural synchronisation is crucial for cognition. The
idea that synchronised temporal patterns between different neural groups carries …

3D-CNN based discrimination of schizophrenia using resting-state fMRI

MNI Qureshi, J Oh, B Lee - Artificial intelligence in medicine, 2019 - Elsevier
Motivation This study reports a framework to discriminate patients with schizophrenia and
normal healthy control subjects, based on magnetic resonance imaging (MRI) of the brain …

Resting state connectivity differences in eyes open versus eyes closed conditions

O Agcaoglu, TW Wilson, YP Wang… - Human brain …, 2019 - Wiley Online Library
Functional magnetic resonance imaging data are commonly collected during the resting
state. Resting state functional magnetic resonance imaging (rs‐fMRI) is very practical and …

Multimodal neuroimaging in schizophrenia: description and dissemination

CJ Aine, HJ Bockholt, JR Bustillo, JM Cañive… - Neuroinformatics, 2017 - Springer
In this paper we describe an open-access collection of multimodal neuroimaging data in
schizophrenia for release to the community. Data were acquired from approximately 100 …

[Retracted] Employing Multimodal Machine Learning for Stress Detection

R Walambe, P Nayak, A Bhardwaj… - Journal of Healthcare …, 2021 - Wiley Online Library
In the current information age, the human lifestyle has become more knowledge‐oriented,
leading to sedentary employment. This has given rise to a number of health and mental …

A brief introduction to magnetoencephalography (MEG) and its clinical applications

AL Fred, SN Kumar, A Kumar Haridhas, S Ghosh… - Brain sciences, 2022 - mdpi.com
Magnetoencephalography (MEG) plays a pivotal role in the diagnosis of brain disorders. In
this review, we have investigated potential MEG applications for analysing brain disorders …