AIMC Topic: Schizophrenia

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Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site FMRI data.

EBioMedicine Aug 13, 2019
BACKGROUND: Current fMRI-based classification approaches mostly use functional connectivity or spatial maps as input, instead of exploring the dynamic time courses directly, which does not leverage the full temporal information.
Young Adult Adult Middle Aged Case-Control Studies Humans Neural Networks, Computer Brain Data Interpretation, Statistical Schizophrenia Schizophrenic Psychology Adolescent ROC Curve Magnetic Resonance Imaging
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Machine learning and big data: Implications for disease modeling and therapeutic discovery in psychiatry.

Artificial intelligence in medicine Aug 9, 2019
INTRODUCTION: Machine learning capability holds promise to inform disease models, the discovery and development of novel disease modifying therapeutics and prevention strategies in psychiatry. Herein, we provide an introduction on how machine learnin...
Decision Trees Models, Biological Schizophrenia Data Mining Psychiatry Precision Medicine Depression Alzheimer Disease Humans Artificial Intelligence Machine Learning Mental Disorders
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Validation of oxidative stress assay for schizophrenia.

Schizophrenia research Aug 6, 2019
Accumulating evidence implicates oxidative stress in a range of diseases, yet no objective measurement has emerged that characterizes the global nature of oxidative stress. Previously, we reported a measurement that employs the moderately strong oxid...
Iridium Machine Learning ROC Curve Biomarkers Humans Biological Assay Female Schizophrenia Reproducibility of Results Adult Male Middle Aged Oxidative Stress
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Classification of schizophrenia and normal controls using 3D convolutional neural network and outcome visualization.

Schizophrenia research Aug 6, 2019
BACKGROUND: The recent deep learning-based studies on the classification of schizophrenia (SCZ) using MRI data rely on manual extraction of feature vector, which destroys the 3D structure of MRI data. In order to both identify SCZ and find relevant b...
Humans Neural Networks, Computer Female Functional Neuroimaging Support Vector Machine Magnetic Resonance Imaging Schizophrenia Young Adult Adult Male Middle Aged
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Identification of the gene signature reflecting schizophrenia's etiology by constructing artificial intelligence-based method of enhanced reproducibility.

CNS neuroscience & therapeutics Jul 27, 2019
AIMS: As one of the most fundamental questions in modern science, "what causes schizophrenia (SZ)" remains a profound mystery due to the absence of objective gene markers. The reproducibility of the gene signatures identified by independent studies i...
Gene Expression Profiling Databases, Genetic Schizophrenia Random Allocation Humans Artificial Intelligence Reproducibility of Results
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3D-CNN based discrimination of schizophrenia using resting-state fMRI.

Artificial intelligence in medicine Jun 22, 2019
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 functional MRI data from a total of 144 subjects (72 pat...
Rest Area Under Curve Young Adult Discriminant Analysis Adult Schizophrenia Male Middle Aged Case-Control Studies Deep Learning Humans Functional Neuroimaging Neural Networks, Computer Magnetic Resonance Imaging Brain Female
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Machine learning identifies unaffected first-degree relatives with functional network patterns and cognitive impairment similar to those of schizophrenia patients.

Human brain mapping May 30, 2019
Schizophrenia (SCZ) patients and their unaffected first-degree relatives (FDRs) share similar functional neuroanatomy. However, it remains largely unknown to what extent unaffected FDRs with functional neuroanatomy patterns similar to patients can be...
Sensitivity and Specificity Male Cognitive Dysfunction Magnetic Resonance Imaging Schizophrenia Cerebellum Pattern Recognition, Automated Cerebral Cortex Biomarkers Female Young Adult Adult Humans Machine Learning Family Connectome Nerve Net
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Analyzing DNA methylation patterns in subjects diagnosed with schizophrenia using machine learning methods.

Journal of psychiatric research Apr 2, 2019
Schizophrenia is a common mental disorder with high heritability. It is genetically complex and to date more than a hundred risk loci have been identified. Association of environmental factors and schizophrenia has also been reported, while epigeneti...
Gene Expression Regulation Humans Middle Aged Machine Learning Case-Control Studies Brain DNA Methylation Female Schizophrenia Male
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Relative importance of symptoms, cognition, and other multilevel variables for psychiatric disease classifications by machine learning.

Psychiatry research Mar 29, 2019
This study used machine-learning algorithms to make unbiased estimates of the relative importance of various multilevel data for classifying cases with schizophrenia (n = 60), schizoaffective disorder (n = 19), bipolar disorder (n = 20), unipolar dep...
Bipolar Disorder Adult Parents Humans Psychotic Disorders Cognition Male Machine Learning Schizophrenia Middle Aged Schizophrenic Psychology Depressive Disorder, Major Female
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Brain Morphometry Methods for Feature Extraction in Random Subspace Ensemble Neural Network Classification of First-Episode Schizophrenia.

Neural computation Mar 18, 2019
Machine learning (ML) is a growing field that provides tools for automatic pattern recognition. The neuroimaging community currently tries to take advantage of ML in order to develop an auxiliary diagnostic tool for schizophrenia diagnostics. In this...
Magnetic Resonance Imaging Schizophrenia Pattern Recognition, Automated Brain Male Humans Diagnosis, Computer-Assisted Neural Networks, Computer
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