Psychiatry

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

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MCDGLN: Masked connection-based dynamic graph learning network for autism spectrum disorder.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by complex physiologic...

Female autism categorization using CNN based NeuroNet57 and ant colony optimization.

Autism identification and classification using biomedical medical image analysis has advanced recent...

Prediction of postpartum depression in women: development and validation of multiple machine learning models.

BACKGROUND: Postpartum depression (PPD) is a significant public health issue. This study aimed to de...

Continuous nursing symptom management in cancer chemotherapy patients using deep learning.

To assess the efficacy of a deep learning platform for managing symptoms in chemotherapy patients, a...

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...

Using Natural Language Processing Methods to Build the Hypersexuality in Bipolar Reddit Corpus: Infodemiology Study of Reddit.

BACKGROUND: Bipolar is a severe mental health condition affecting at least 2% of the global populati...

Applying AI in the Context of the Association Between Device-Based Assessment of Physical Activity and Mental Health: Systematic Review.

BACKGROUND: Wearable technology is used by consumers worldwide for continuous activity monitoring in...

AI anxiety and knowledge payment: the roles of perceived value and self-efficacy.

BACKGROUND: The integration of Artificial Intelligence (AI) into daily life raises significant chall...

On-Chip Mental Stress Detection: Integrating a Wearable Behind-The-Ear EEG Device With Embedded Tiny Neural Network.

The study introduces an innovative approach to efficient mental stress detection by combining electr...

AdaptEEG: A Deep Subdomain Adaptation Network With Class Confusion Loss for Cross-Subject Mental Workload Classification.

EEG signals exhibit non-stationary characteristics, particularly across different subjects, which pr...

Research on prediction model of adolescent suicide and self-injury behavior based on machine learning algorithm.

OBJECTIVE: To explore the risk factors that affect adolescents' suicidal and self-injurious behavior...

Involvement of disulfidptosis in the pathophysiology of autism spectrum disorder.

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder, with oxidative stress recog...

A machine learning approach to predict treatment efficacy and adverse effects in major depression using CYP2C19 and clinical-environmental predictors.

BACKGROUND: Major depressive disorder (MDD) is among the leading causes of disability worldwide and ...

Cognitive biases in forensic psychiatry: A scoping review.

Forensic psychiatry plays a critical role in legal contexts but is highly susceptible to cognitive b...

Real-time monitoring to predict depressive symptoms: study protocol.

INTRODUCTION: According to the World Health Organization, Depression is the fourth leading cause of ...

Morphological alterations of the thymus gland in individuals with schizophrenia.

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

Circadian rhythm modulation in heart rate variability as potential biomarkers for major depressive disorder: A machine learning approach.

Major depressive disorder (MDD) is associated with reduced heart rate variability (HRV), but its lin...

miRNA-Based Diagnosis of Schizophrenia Using Machine Learning.

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

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