Psychiatry

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

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An integrated ergonomic risk assessment framework based on fuzzy logic and IVSF-AHP for optimising ergonomic risks in a mixed-model assembly line.

This study proposes a systematic approach to address ergonomic factors, including physical, environm...

Predicting long-term sleep deprivation using wearable sensors and health surveys.

Sufficient sleep is essential for individual well-being. Inadequate sleep has been shown to have sig...

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...

A Deep Learning Approach to Estimate Multi-Level Mental Stress From EEG Using Serious Games.

Stress is revealed by the inability of individuals to cope with their environment, which is frequent...

Factors influencing psychological distress among breast cancer survivors using machine learning techniques.

Breast cancer is the most commonly diagnosed cancer among women worldwide. Breast cancer patients ex...

Identifying subgroups of urge suppression in Obsessive-Compulsive Disorder using machine learning.

Obsessive-compulsive disorder (OCD) is phenomenologically heterogeneous. While predominant models su...

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...

Tai Chi Movement Recognition and Precise Intervention for the Elderly Based on Inertial Measurement Units and Temporal Convolutional Neural Networks.

(1) Background: The objective of this study was to recognize tai chi movements using inertial measur...

Multilayer Perceptron-Based Wearable Exercise-Related Heart Rate Variability Predicts Anxiety and Depression in College Students.

(1) Background: This study aims to investigate the correlation between heart rate variability (HRV) ...

Evaluating generative AI responses to real-world drug-related questions.

Generative Artificial Intelligence (AI) systems such as OpenAI's ChatGPT, capable of an unprecedente...

Predictive modelling of stress, anxiety and depression: A network analysis and machine learning study.

OBJECTIVE: This study assessed predictors of stress, anxiety and depression during the COVID-19 pand...

Enhancing Aviation Safety through AI-Driven Mental Health Management for Pilots and Air Traffic Controllers.

This article provides an overview of the mental health challenges faced by pilots and air traffic co...

On new common fixed point theorems via bipolar fuzzy -metric space with their applications.

This research work is devoted to investigating new common fixed point theorems on bipolar fuzzy -met...

Three autism subtypes based on single-subject gray matter network revealed by semi-supervised machine learning.

Autism spectrum disorder (ASD) is a heterogeneous, early-onset neurodevelopmental condition characte...

Machine learning for antidepressant treatment selection in depression.

Finding the right antidepressant for the individual patient with major depressive disorder can be a ...

Artificial intelligence in the era of planetary health: insights on its application for the climate change-mental health nexus in the Philippines.

This review explores the transformative potential of Artificial Intelligence (AI) in the light of ev...

Network-based artificial intelligence approaches for advancing personalized psychiatry.

Psychiatric disorders have a complex biological underpinning likely involving an interplay of geneti...

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

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

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