Psychiatry

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

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AI simulation models for diagnosing disabilities in smart electrical prosthetics using bipolar fuzzy decision making based on choquet integral.

The integration of AI simulation models within smart electrical prosthetic systems represents a sign...

Neurobehavioral mechanisms of fear and anxiety in multiple sclerosis.

BACKGROUND: Anxiety is a common yet often underdiagnosed and undertreated comorbidity in multiple sc...

Application of causal forest double machine learning (DML) approach to assess tuberculosis preventive therapy's impact on ART adherence.

Adherence to antiretroviral therapy (ART) is critical for HIV treatment success, yet the impact of t...

Exposotypes in psychotic disorders.

Psychiatry lags in adopting etiological approaches to diagnosis, prognosis, and outcome prediction c...

A Study on the Synaptic Behavior of Al/ZrO/TiO/Al Electronic Bipolar Resistance Switching Memristor.

This study presents the Al/ZrO/TiO/Al (AZTA) memristor, a device based on a nonfilamentary mechanism...

The Effectiveness and Feasibility of Conversational Agents in Supporting Care for Patients With Cancer: Systematic Review and Meta-Analysis.

BACKGROUND: Patients with cancer experience complex physical, psychosocial, and behavioral challenge...

Computational mechanisms of neuroimaging biomarkers uncovered by multicenter resting-state fMRI connectivity variation profile.

Resting-state functional connectivity (rsFC) is increasingly used to develop biomarkers for psychiat...

Cross-Platform Availability of Smartphone Sensors for Depression Indication Systems: Mixed-Methods Umbrella Review.

BACKGROUND: A popular trend in depression forecasting research is the development of machine learnin...

Integrated 3D Modeling and Functional Simulation of the Human Amygdala: A Novel Anatomical and Computational Analyses.

The amygdala plays a central role in emotion, memory, and decision-making and comprises approximatel...

Predicting post-traumatic stress disorder in relatives of critically ill patients.

PURPOSE OF REVIEW: Symptoms of posttraumatic stress disorder (PTSD) affect up to a third of relative...

Developing personalized algorithms for sensing mental health symptoms in daily life.

The integration of artificial intelligence (AI) and pervasive computing offers new opportunities to ...

A novel approach to smart-assisted schizophrenia screening based on Raman spectroscopy and deep learning.

In this study, serum Raman spectra are introduced into the screening of schizophrenia. We collect se...

Development and interpretation of a machine learning risk prediction model for post-stroke depression in a Chinese population.

Current evidence for predictive models of post-stroke depression (PSD) risk based on machine learnin...

Clinical correlates of errors in machine-learning diagnostic model of autism spectrum disorder: Impact of sample cohorts.

Machine-learning models can assist in diagnosing autism but have biases. We examines the correlates ...

Enhancing Electroencephalogram-Based Prediction of Posttraumatic Stress Disorder Treatment Response Using Data Augmentation.

OBJECTIVE: This study aimed to improve the prediction of treatment response in patients with posttra...

An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders.

BACKGROUND: Niacin Skin-Flushing Response (NSR) has emerged as a promising objective biomarker for t...

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