AIMC Topic: Schizophrenia

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A review on neural network models of schizophrenia and autism spectrum disorder.

Neural networks : the official journal of the International Neural Network Society Nov 13, 2019
This survey presents the most relevant neural network models of autism spectrum disorder and schizophrenia, from the first connectionist models to recent deep neural network architectures. We analyzed and compared the most representative symptoms wit...
Neural Networks, Computer Autism Spectrum Disorder Bayes Theorem Humans Schizophrenia Connectome
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Guest editorial: Special issue on machine learning in schizophrenia.

Schizophrenia research Nov 9, 2019
Machine Learning Schizophrenia Psychotic Disorders Neuroimaging Humans
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Decentralized distribution-sampled classification models with application to brain imaging.

Journal of neuroscience methods Oct 17, 2019
BACKGROUND: In this age of big data, certain models require very large data stores in order to be informative and accurate. In many cases however, the data are stored in separate locations requiring data transfer between local sites which can cause v...
Neuroimaging Models, Statistical Schizophrenia Datasets as Topic Female Humans Adult Brain Male Support Vector Machine Deep Learning Magnetic Resonance Imaging Models, Theoretical
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Multivariate classification of schizophrenia and its familial risk based on load-dependent attentional control brain functional connectivity.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology Oct 3, 2019
Patients with schizophrenia (SCZ), as well as their unaffected siblings (SIB), show functional connectivity (FC) alterations during performance of tasks involving attention. As compared with SCZ, these alterations are present in SIB to a lesser exten...
Nerve Net Schizophrenic Psychology Attention Multivariate Analysis Neuropsychological Tests Brain Female Risk Factors Humans Magnetic Resonance Imaging Machine Learning Schizophrenia Adult Male
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Use of Natural Language Processing to identify Obsessive Compulsive Symptoms in patients with schizophrenia, schizoaffective disorder or bipolar disorder.

Scientific reports Oct 2, 2019
Obsessive and Compulsive Symptoms (OCS) or Obsessive Compulsive Disorder (OCD) in the context of schizophrenia or related disorders are of clinical importance as these are associated with a range of adverse outcomes. Natural Language Processing (NLP)...
Humans Comorbidity Bipolar Disorder Natural Language Processing Schizophrenia Female Adult Male Database Management Systems Obsessive-Compulsive Disorder Psychotic Disorders Medical Records Systems, Computerized Clinical Coding
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Generalizability of machine learning for classification of schizophrenia based on resting-state functional MRI data.

Human brain mapping Oct 1, 2019
Machine learning has increasingly been applied to classification of schizophrenia in neuroimaging research. However, direct replication studies and studies seeking to investigate generalizability are scarce. To address these issues, we assessed withi...
Schizophrenia Connectome Female Humans Reproducibility of Results Magnetic Resonance Imaging Adult Male Unsupervised Machine Learning Middle Aged
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A Multi-Domain Connectome Convolutional Neural Network for Identifying Schizophrenia From EEG Connectivity Patterns.

IEEE journal of biomedical and health informatics Sep 13, 2019
OBJECTIVE: We exploit altered patterns in brain functional connectivity as features for automatic discriminative analysis of neuropsychiatric patients. Deep learning methods have been introduced to functional network classification only very recently...
Adolescent Child Electroencephalography Connectome Signal Processing, Computer-Assisted Schizophrenia Neural Networks, Computer Diagnosis, Computer-Assisted Deep Learning Humans
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Using machine learning to explain the heterogeneity of schizophrenia. Realizing the promise and avoiding the hype.

Schizophrenia research Sep 6, 2019
Despite extensive research and prodigious advances in neuroscience, our comprehension of the nature of schizophrenia remains rudimentary. Our failure to make progress is attributed to the extreme heterogeneity of this condition, enormous complexity o...
Humans Neurosciences Machine Learning Psychiatry Schizophrenia
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Identifying schizophrenia subgroups using clustering and supervised learning.

Schizophrenia research Aug 24, 2019
Schizophrenia has a 1% incidence rate world-wide and those diagnosed present with positive (e.g. hallucinations, delusions), negative (e.g. apathy, asociality), and cognitive symptoms. However, both symptom burden and associated brain alterations are...
Image Interpretation, Computer-Assisted Pattern Recognition, Automated Psychiatric Status Rating Scales Adult Humans Supervised Machine Learning Male Organ Size Magnetic Resonance Imaging Brain Schizophrenia Area Under Curve Cluster Analysis Severity of Illness Index Female
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Characterizing functional regional homogeneity (ReHo) as a B-SNIP psychosis biomarker using traditional and machine learning approaches.

Schizophrenia research Aug 19, 2019
BACKGROUND: Recently, a biologically-driven psychosis classification (B-SNIP Biotypes) was derived using brain-based cognitive and electrophysiological markers. Here, we characterized a local functional-connectivity measure, regional homogeneity (ReH...
Biomarkers Brain Psychotic Disorders Female Connectome Bipolar Disorder Adult Magnetic Resonance Imaging Humans Support Vector Machine Schizophrenia Male Middle Aged
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