AIMC Topic: Schizophrenia
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CNVDeep: deep association of copy number variants with neurocognitive disorders.
BMC bioinformatics
Aug 29, 2024
BACKGROUND: Copy number variants (CNVs) have become increasingly instrumental in understanding the etiology of all diseases and phenotypes, including Neurocognitive Disorders (NDs). Among the well-established regions associated with ND are small part...
Schizophrenia diagnosis using the GRU-layer's alpha-EEG rhythm's dependability.
Psychiatry research. Neuroimaging
Aug 28, 2024
Verifying schizophrenia (SZ) can be assisted by deep learning techniques and patterns in brain activity observed in alpha-EEG recordings. The suggested research provides evidence of the reliability of alpha-EEG rhythm in a Gated-Recurrent-Unit-based ...
Immune-based Machine learning Prediction of Diagnosis and Illness State in Schizophrenia and Bipolar Disorder.
Brain, behavior, and immunity
Aug 14, 2024
BACKGROUND: Schizophrenia and bipolar disorder frequently face significant delay in diagnosis, leading to being missed or misdiagnosed in early stages. Both disorders have also been associated with trait and state immune abnormalities. Recent machine...
Enhancing schizophrenia phenotype prediction from genotype data through knowledge-driven deep neural network models.
Genomics
Aug 5, 2024
This article explores deep learning model design, drawing inspiration from the omnigenic model and genetic heterogeneity concepts, to improve schizophrenia prediction using genotype data. It introduces an innovative three-step approach leveraging neu...
Assessing dimensions of thought disorder with large language models: The tradeoff of accuracy and consistency.
Psychiatry research
Aug 3, 2024
Natural Language Processing (NLP) methods have shown promise for the assessment of formal thought disorder, a hallmark feature of schizophrenia in which disturbances to the structure, organization, or coherence of thought can manifest as disordered o...
Detecting outliers in case-control cohorts for improving deep learning networks on Schizophrenia prediction.
Journal of integrative bioinformatics
Jul 15, 2024
This study delves into the intricate genetic and clinical aspects of Schizophrenia, a complex mental disorder with uncertain etiology. Deep Learning (DL) holds promise for analyzing large genomic datasets to uncover new risk factors. However, based o...
Role of different omics data in the diagnosis of schizophrenia disorder: A machine learning study.
Schizophrenia research
Jul 14, 2024
Schizophrenia is a serious mental disorder that affects millions of people worldwide. This disorder slowly disintegrates thinking ability and changes behaviours of patients. These patients will show some psychotic symptoms such as hallucinations, del...
Identification and diagnosis of schizophrenia based on multichannel EEG and CNN deep learning model.
Schizophrenia research
Jul 14, 2024
This paper proposes a high-accuracy EEG-based schizophrenia (SZ) detection approach. Unlike comparable literature studies employing conventional machine learning algorithms, our method autonomously extracts the necessary features for network training...
Deep learning for schizophrenia classification based on natural language processing-A pilot study.
Schizophrenia research
Jul 3, 2024
Wavelet Transform, Reconstructed Phase Space, and Deep Learning Neural Networks for EEG-Based Schizophrenia Detection.
International journal of neural systems
Jun 28, 2024
This study proposes an innovative expert system that uses exclusively EEG signals to diagnose schizophrenia in its early stages. For diagnosing psychiatric/neurological disorders, electroencephalogram (EEG) testing is considered a financially viable,...
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