AIMC Topic: Schizophrenia
Clear Filters Showing 211 to 220 of 286 articles
Deep dreaming, aberrant salience and psychosis: Connecting the dots by artificial neural networks.
Schizophrenia research
Jan 24, 2017
Why some individuals, when presented with unstructured sensory inputs, develop altered perceptions not based in reality, is not well understood. Machine learning approaches can potentially help us understand how the brain normally interprets sensory ...
Using deep belief network modelling to characterize differences in brain morphometry in schizophrenia.
Scientific reports
Dec 12, 2016
Neuroimaging-based models contribute to increasing our understanding of schizophrenia pathophysiology and can reveal the underlying characteristics of this and other clinical conditions. However, the considerable variability in reported neuroimaging ...
Advanced literature analysis in a Big Data world.
Annals of the New York Academy of Sciences
Nov 10, 2016
Comprehensive data mining of the scientific literature has become an increasing challenge. To address this challenge, Elsevier's Pathway Studio software uses the techniques of natural language processing to systematically extract specific biological ...
Mental Disorders
Biomarkers
Prognosis
Biomedical Research
Animals
Humans
Software
Schizophrenia
Data Mining
Abstracting and Indexing
National Institute of Mental Health (U.S.)
Database Management Systems
Databases, Bibliographic
United States
Mass Screening
Natural Language Processing
Depressive Disorder, Major
Periodicals as Topic
Anxiety Disorders
Translational Research, Biomedical
Bipolar Disorder
Computational Biology
Connectivity of the anterior insula differentiates participants with first-episode schizophrenia spectrum disorders from controls: a machine-learning study.
Psychological medicine
Jul 25, 2016
BACKGROUND: Early diagnosis of schizophrenia could improve the outcomes and limit the negative effects of untreated illness. Although participants with schizophrenia show aberrant functional connectivity in brain networks, these between-group differe...
Machine-learning-based diagnosis of schizophrenia using combined sensor-level and source-level EEG features.
Schizophrenia research
Jul 15, 2016
Recently, an increasing number of researchers have endeavored to develop practical tools for diagnosing patients with schizophrenia using machine learning techniques applied to EEG biomarkers. Although a number of studies showed that source-level EEG...
Dynamic cerebral reorganization in the pathophysiology of schizophrenia: a MRI-derived cortical thickness study.
Psychological medicine
May 26, 2016
BACKGROUND: A structural neuroanatomical change indicating a reduction in brain tissue is a notable feature of schizophrenia. Several pathophysiological processes such as aberrant cortical maturation, progressive tissue loss and compensatory tissue i...
A hierarchical model for integrating unsupervised generative embedding and empirical Bayes.
Journal of neuroscience methods
Apr 30, 2016
BACKGROUND: Generative models of neuroimaging data, such as dynamic causal models (DCMs), are commonly used for inferring effective connectivity from individual subject data. Recently introduced "generative embedding" approaches have used DCM-based c...
Accelerated Brain Aging in Schizophrenia: A Longitudinal Pattern Recognition Study.
The American journal of psychiatry
Feb 26, 2016
OBJECTIVE: Despite the multitude of longitudinal neuroimaging studies that have been published, a basic question on the progressive brain loss in schizophrenia remains unaddressed: Does it reflect accelerated aging of the brain, or is it caused by a ...
A multi-layer network approach to MEG connectivity analysis.
NeuroImage
Feb 22, 2016
Recent years have shown the critical importance of inter-regional neural network connectivity in supporting healthy brain function. Such connectivity is measurable using neuroimaging techniques such as MEG, however the richness of the electrophysiolo...
Prediction of psychosis using neural oscillations and machine learning in neuroleptic-naïve at-risk patients.
The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry
Oct 9, 2015
OBJECTIVES: This study investigates whether abnormal neural oscillations, which have been shown to precede the onset of frank psychosis, could be used towards the individualised prediction of psychosis in clinical high-risk patients.
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