AIMC Topic: Schizophrenia

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Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia.

Nature neuroscience Jan 11, 2021
Retrotransposons can cause somatic genome variation in the human nervous system, which is hypothesized to have relevance to brain development and neuropsychiatric disease. However, the detection of individual somatic mobile element insertions present...
Genome Neuroglia Cation Transport Proteins Retroelements High-Throughput Nucleotide Sequencing HeLa Cells Embryonic Development Mutagenesis, Insertional Mental Disorders Pregnancy Female Adult Long Interspersed Nucleotide Elements Adaptor Proteins, Signal Transducing Neurons Schizophrenia Humans Machine Learning
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Identification of Children at Risk of Schizophrenia via Deep Learning and EEG Responses.

IEEE journal of biomedical and health informatics Jan 5, 2021
The prospective identification of children likely to develop schizophrenia is a vital tool to support early interventions that can mitigate the risk of progression to clinical psychosis. Electroencephalographic (EEG) patterns from brain activity and ...
Deep Learning Child Electroencephalography Schizophrenia Humans Neural Networks, Computer Prospective Studies
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The machine learning algorithm for the diagnosis of schizophrenia on the basis of gene expression in peripheral blood.

Neuroscience letters Dec 24, 2020
BACKGROUND: Schizophrenia (SCZ) is a highly heritable mental disorder with a substantial disease burden. Machine learning (ML) method can be used to identify individuals with SCZ on the basis of blood gene expression data with high accuracy.
Machine Learning Algorithms Female Adult Humans Asian People Male Schizophrenia RNA, Messenger Gene Expression
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Support vector machine-based classification of schizophrenia patients and healthy controls using structural magnetic resonance imaging from two independent sites.

PloS one Nov 24, 2020
Structural brain alterations have been repeatedly reported in schizophrenia; however, the pathophysiology of its alterations remains unclear. Multivariate pattern recognition analysis such as support vector machines can classify patients and healthy ...
Schizophrenia Humans Male Cerebral Cortex Female Prefrontal Cortex Adult Support Vector Machine Magnetic Resonance Imaging
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Comparing machine and deep learning-based algorithms for prediction of clinical improvement in psychosis with functional magnetic resonance imaging.

Human brain mapping Nov 13, 2020
Previous work using logistic regression suggests that cognitive control-related frontoparietal activation in early psychosis can predict symptomatic improvement after 1 year of coordinated specialty care with 66% accuracy. Here, we evaluated the abil...
Follow-Up Studies Magnetic Resonance Imaging Schizophrenia Outcome Assessment, Health Care Adolescent Bipolar Disorder Support Vector Machine Psychomotor Performance Dorsolateral Prefrontal Cortex Executive Function Humans Machine Learning Female Young Adult Adult Male Deep Learning Functional Neuroimaging
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Characterization of specific and distinct patient types in clinical trials of acute schizophrenia using an uncorrelated PANSS score matrix transform (UPSM).

Psychiatry research Nov 11, 2020
Understanding the specificity of symptom change in schizophrenia can facilitate the evaluation antipsychotic efficacy for different symptom domains. Previous work identified a transform of PANSS using an uncorrelated PANSS score matrix (UPSM) to redu...
Double-Blind Method Schizophrenia Antipsychotic Agents Schizophrenic Psychology Male Humans Psychiatric Status Rating Scales Machine Learning Treatment Outcome Female Adult
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Big data in severe mental illness: the role of electronic monitoring tools and metabolomics.

Personalized medicine Oct 30, 2020
There is an increasing interest in the development of effective early detection and intervention strategies in severe mental illness (SMI). Ideally, these efforts should lead to the delineation of accurate staging models of SMI enabling personalized ...
Metabolomics Remote Sensing Technology Mental Disorders Schizophrenia Depressive Disorder, Major Early Diagnosis Big Data Humans Bipolar Disorder Machine Learning
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Inner speech.

Wiley interdisciplinary reviews. Cognitive science Sep 18, 2020
Inner speech travels under many aliases: the inner voice, verbal thought, thinking in words, internal verbalization, "talking in your head," the "little voice in the head," and so on. It is both a familiar element of first-person experience and a psy...
Humans Artificial Intelligence Cognitive Science Hallucinations Brain Speech Schizophrenia Consciousness
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Multi-dimensional predictions of psychotic symptoms via machine learning.

Human brain mapping Sep 1, 2020
The diagnostic criteria for schizophrenia comprise a diverse range of heterogeneous symptoms. As a result, individuals each present a distinct set of symptoms despite having the same overall diagnosis. Whilst previous machine learning studies have pr...
Adolescent Adult Magnetic Resonance Imaging Humans Auditory Perception Male Schizophrenia Machine Learning Prognosis Middle Aged Psychotic Disorders Attention Functional Neuroimaging Female Motivation Young Adult Anhedonia Hallucinations
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Predicting Early Warning Signs of Psychotic Relapse From Passive Sensing Data: An Approach Using Encoder-Decoder Neural Networks.

JMIR mHealth and uHealth Aug 31, 2020
BACKGROUND: Schizophrenia spectrum disorders (SSDs) are chronic conditions, but the severity of symptomatic experiences and functional impairments vacillate over the course of illness. Developing unobtrusive remote monitoring systems to detect early ...
Recurrence Humans Text Messaging Middle Aged Female Neural Networks, Computer Smartphone Young Adult Schizophrenia Adult Male
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