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 …
Neuroimaging-based biomarkers in psychiatry: clinical opportunities of a paradigm shift
CHY Fu, SG Costafreda - The Canadian Journal of …, 2013 - journals.sagepub.com
Neuroimaging research has substantiated the functional and structural abnormalities
underlying psychiatric disorders but has, thus far, failed to have a significant impact on …
underlying psychiatric disorders but has, thus far, failed to have a significant impact on …
Classification of schizophrenia and bipolar patients using static and dynamic resting-state fMRI brain connectivity
Recently, functional network connectivity (FNC, defined as the temporal correlation among
spatially distant brain networks) has been used to examine the functional organization of …
spatially distant brain networks) has been used to examine the functional organization of …
Classification of schizophrenia patients based on resting-state functional network connectivity
There is a growing interest in automatic classification of mental disorders based on
neuroimaging data. Small training data sets (subjects) and very large amount of high …
neuroimaging data. Small training data sets (subjects) and very large amount of high …
High classification accuracy for schizophrenia with rest and task fMRI data
We present a novel method to extract classification features from functional magnetic
resonance imaging (fMRI) data collected at rest or during the performance of a task. By …
resonance imaging (fMRI) data collected at rest or during the performance of a task. By …
Multimodal neuroimaging: basic concepts and classification of neuropsychiatric diseases
Neuroimaging techniques are widely used in neuroscience to visualize neural activity, to
improve our understanding of brain mechanisms, and to identify biomarkers—especially for …
improve our understanding of brain mechanisms, and to identify biomarkers—especially for …
Diffusion tensor imaging reliably differentiates patients with schizophrenia from healthy volunteers
BA Ardekani, A Tabesh, S Sevy… - Human brain …, 2011 - Wiley Online Library
The objective of this research was to determine whether fractional anisotropy (FA) and mean
diffusivity (MD) maps derived from diffusion tensor imaging (DTI) of the brain are able to …
diffusivity (MD) maps derived from diffusion tensor imaging (DTI) of the brain are able to …
A review of challenges in the use of fMRI for disease classification/characterization and a projection pursuit application from a multi-site fMRI schizophrenia study
O Demirci, VP Clark, VA Magnotta… - Brain imaging and …, 2008 - Springer
Functional magnetic resonance imaging (fMRI) is a fairly new technique that has the
potential to characterize and classify brain disorders such as schizophrenia. It has the …
potential to characterize and classify brain disorders such as schizophrenia. It has the …
Feature and decision-level fusion for schizophrenia detection based on resting-state fMRI data
Mental disorders, especially schizophrenia, still pose a great challenge for diagnosis in early
stages. Recently, computer-aided diagnosis techniques based on resting-state functional …
stages. Recently, computer-aided diagnosis techniques based on resting-state functional …
Multi-center machine learning in imaging psychiatry: a meta-model approach
One of the biggest problems in automated diagnosis of psychiatric disorders from medical
images is the lack of sufficiently large samples for training. Sample size is especially …
images is the lack of sufficiently large samples for training. Sample size is especially …