Schizophrenia

Optimizing biomedical information retrieval with a keyword frequency-driven prompt enhancement strategy.

BACKGROUND: Mining the vast pool of biomedical literature to extract accurate responses and relevant...

The state of artificial intelligence in medical research: A survey of corresponding authors from top medical journals.

Natural Language Processing (NLP) is a subset of artificial intelligence that enables machines to un...

Immune-based Machine learning Prediction of Diagnosis and Illness State in Schizophrenia and Bipolar Disorder.

BACKGROUND: Schizophrenia and bipolar disorder frequently face significant delay in diagnosis, leadi...

Generative Artificial Intelligence and Large Language Models in Primary Care Medical Education.

Generative artificial intelligence and large language models are the continuation of a technological...

Development of an eye-tracking system based on a deep learning model to assess executive function in patients with mental illnesses.

Patients with mental illnesses, particularly psychosis and obsessive‒compulsive disorder (OCD), freq...

Enhancing schizophrenia phenotype prediction from genotype data through knowledge-driven deep neural network models.

This article explores deep learning model design, drawing inspiration from the omnigenic model and g...

Assessing dimensions of thought disorder with large language models: The tradeoff of accuracy and consistency.

Natural Language Processing (NLP) methods have shown promise for the assessment of formal thought di...

Unlocking treatment success: predicting atypical antipsychotic continuation in youth with mania.

PURPOSE: This study aimed to create and validate robust machine-learning-based prediction models for...

Neural waves and computation in a neural net model II: Data-like structures and the dynamics of episodic memory.

The computational resources of a neuromorphic network model introduced earlier were investigated in ...

Natural language processing in at-risk mental states: enhancing the assessment of thought disorders and psychotic traits with semantic dynamics and graph theory.

OBJECTIVE: Verbal communication contains key information for mental health assessment. Researchers h...

Adaptive node feature extraction in graph-based neural networks for brain diseases diagnosis using self-supervised learning.

Electroencephalography (EEG) has demonstrated significant value in diagnosing brain diseases. In par...

Detecting outliers in case-control cohorts for improving deep learning networks on Schizophrenia prediction.

This study delves into the intricate genetic and clinical aspects of Schizophrenia, a complex mental...

Role of different omics data in the diagnosis of schizophrenia disorder: A machine learning study.

Schizophrenia is a serious mental disorder that affects millions of people worldwide. This disorder ...

Identification and diagnosis of schizophrenia based on multichannel EEG and CNN deep learning model.

This paper proposes a high-accuracy EEG-based schizophrenia (SZ) detection approach. Unlike comparab...

Lung Adenocarcinoma Systems Biomarker and Drug Candidates Identified by Machine Learning, Gene Expression Data, and Integrative Bioinformatics Pipeline.

Lung adenocarcinoma (LUAD) is a significant planetary health challenge with its high morbidity and m...

Using Human Resources Data to Predict Turnover of Community Mental Health Employees: Prediction and Interpretation of Machine Learning Methods.

This study used machine learning (ML) to predict mental health employees' turnover in the following ...

Deep learning for schizophrenia classification based on natural language processing-A pilot study.

Power spectral density-based resting-state EEG classification of first-episode psychosis.

Historically, the analysis of stimulus-dependent time-frequency patterns has been the cornerstone of...

Wavelet Transform, Reconstructed Phase Space, and Deep Learning Neural Networks for EEG-Based Schizophrenia Detection.

This study proposes an innovative expert system that uses exclusively EEG signals to diagnose schizo...

Glycocalyx shedding patterns identifies antipsychotic-naïve patients with first-episode psychosis.

Psychotic disorders have been linked to immune-system abnormalities, increased inflammatory markers,...

A Machine Learning Framework for Screening Plasma Cell-Associated Feature Genes to Estimate Osteoporosis Risk and Treatment Vulnerability.

Osteoporosis, in which bones become fragile owing to low bone density and impaired bone mass, is a g...