An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future …
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 …
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
Brain functional imaging data, especially functional magnetic resonance imaging (fMRI)
data, have been employed to reflect functional integration of the brain. Alteration in brain …
data, have been employed to reflect functional integration of the brain. Alteration in brain …
Evidence for embracing normative modeling
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 …
2022a to include normative models charting lifespan trajectories of structural surface area …
Towards a brain‐based predictome of mental illness
Neuroimaging‐based approaches have been extensively applied to study mental illness in
recent years and have deepened our understanding of both cognitively healthy and …
recent years and have deepened our understanding of both cognitively healthy and …
Dynamics of large-scale electrophysiological networks: A technical review
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 …
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 …
normal healthy control subjects, based on magnetic resonance imaging (MRI) of the brain …
Resting state connectivity differences in eyes open versus eyes closed conditions
Functional magnetic resonance imaging data are commonly collected during the resting
state. Resting state functional magnetic resonance imaging (rs‐fMRI) is very practical and …
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 …
schizophrenia for release to the community. Data were acquired from approximately 100 …
[Retracted] Employing Multimodal Machine Learning for Stress Detection
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 …
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
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 …
this review, we have investigated potential MEG applications for analysing brain disorders …