Psychiatry

Schizophrenia

Latest AI and machine learning research in schizophrenia for healthcare professionals.

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An ensemble approach using multidimensional convolutional neural networks in wavelet domain for schizophrenia classification from sMRI data.

Schizophrenia is a complicated mental condition marked by disruptions in thought processes, percepti...

Deep Learning-Assisted SERS for Therapeutic Drug Monitoring of Clozapine in Serum on Plasmonic Metasurfaces.

Clozapine is widely regarded as one of the most effective therapeutics for treatment-resistant schiz...

GPT-4 generated psychological reports in psychodynamic perspective: a pilot study on quality, risk of hallucination and client satisfaction.

BACKGROUND: Recently, there have been active proposals on how to utilize large language models (LLMs...

Exploring the significance of the frontal lobe for diagnosis of schizophrenia using explainable artificial intelligence and group level analysis.

Schizophrenia (SZ) is a complex mental disorder characterized by a profound disruption in cognition ...

The More, the Better? Evaluating the Role of EEG Preprocessing for Deep Learning Applications.

The last decade has witnessed a notable surge in deep learning applications for electroencephalograp...

Morphological alterations of the thymus gland in individuals with schizophrenia.

Despite its critical function in the immune system and accumulating evidence of immunological abnorm...

miRNA-Based Diagnosis of Schizophrenia Using Machine Learning.

Diagnostic practices for schizophrenia are unreliable due to the lack of a stable biomarker. However...

Comprehensive evaluation of pipelines for classification of psychiatric disorders using multi-site resting-state fMRI datasets.

Objective classification biomarkers that are developed using resting-state functional magnetic reson...

Joint Driver State Classification Approach: Face Classification Model Development and Facial Feature Analysis Improvement.

Driver drowsiness remains a critical factor in road safety, necessitating the development of robust ...

Neurofind: using deep learning to make individualised inferences in brain-based disorders.

Within precision psychiatry, there is a growing interest in normative models given their ability to ...

Interpretable modality-specific and interactive graph convolutional network on brain functional and structural connectomes.

Both brain functional connectivity (FC) and structural connectivity (SC) provide distinct neural mec...

Identifying periphery biomarkers of first-episode drug-naïve patients with schizophrenia using machine-learning-based strategies.

Schizophrenia is a complex mental disorder. Accurate diagnosis and classification of schizophrenia h...

Electroencephalogram (EEG) Based Fuzzy Logic and Spiking Neural Networks (FLSNN) for Advanced Multiple Neurological Disorder Diagnosis.

Neurological disorders are a major global health concern that have a substantial impact on death rat...

Deep learning imputes DNA methylation states in single cells and enhances the detection of epigenetic alterations in schizophrenia.

DNA methylation (DNAm) is a key epigenetic mark with essential roles in gene regulation, mammalian d...

Predicting mental health disparities using machine learning for African Americans in Southeastern Virginia.

This study examined mental health disparities among African Americans using AI and machine learning ...

Efficient Neural Network Classification of Parkinson's Disease and Schizophrenia Using Resting-State EEG Data.

Timely identification of Parkinson's disease and schizophrenia is crucial for the effective manageme...

Predicting antipsychotic responsiveness using a machine learning classifier trained on plasma levels of inflammatory markers in schizophrenia.

We apply machine learning techniques to navigate the multifaceted landscape of schizophrenia. Our me...

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