Psychiatry

Anxiety & Stress

Latest AI and machine learning research in anxiety & stress for healthcare professionals.

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Machine learning reveals connections between preclinical type 2 diabetes subtypes and brain health.

Previous research has established type 2 diabetes mellitus as a significant risk factor for various ...

Using Machine Learning to Predict Uptake to an Online Self-Guided Intervention for Stress During the COVID-19 Pandemic.

Online self-guided interventions appear efficacious for alleviating some mental health concerns. How...

A psychologically interpretable artificial intelligence framework for the screening of loneliness, depression, and anxiety.

Negative emotions such as loneliness, depression, and anxiety (LDA) are prevalent and pose significa...

ML-ROM wall shear stress prediction in patient-specific vascular pathologies under a limited clinical training data regime.

High-fidelity numerical simulations such as Computational Fluid Dynamics (CFD) have been proven effe...

Personalization variables in digital mental health interventions for depression and anxiety in adolescents and youth: a scoping review.

INTRODUCTION: The impact of personalization on user engagement and adherence in digital mental healt...

From the -Factor to Cognitive Content: Detection and Discrimination of Psychopathologies Based on Explainable Artificial Intelligence.

Differentiating psychopathologies is challenging due to shared underlying mechanisms, such as the -...

Intimate partner violence and stress-related disorders: from epigenomics to resilience.

Intimate Partner Violence (IPV) is a major public health problem to be addressed with innovative and...

Machine Learning Models to Identify Clinically Significant Anxiety in Short-Term Insomnia Using Accelerometers.

Clinically significant anxiety (CSA) is common in individuals with short-term insomnia. This study a...

Predicting Suicidal Ideation Among Youths With Autism Spectrum Disorder: An Advanced Machine Learning Study.

This study aimed to predict suicidal ideation among youth with autism spectrum disorder (ASD) by app...

Predicting depression severity using machine learning models: Insights from mitochondrial peptides and clinical factors.

Depression presents a significant challenge to global mental health, often intertwined with factors ...

A Machine Learning Model Using Cardiac CT and MRI Data Predicts Cardiovascular Events in Obstructive Coronary Artery Disease.

Background Multimodality imaging is essential for personalized prognostic stratification in suspecte...

[Optimization of centrifugal artificial heart pump blade parameters based on back propagation neural network and grey wolf optimization algorithm].

The impeller, as a key component of artificial heart pumps, experiences high shear stress due to its...

[A study on post-traumatic stress disorder classification based on multi-atlas multi-kernel graph convolutional network].

Post-traumatic stress disorder (PTSD) presents with complex and diverse clinical manifestations, mak...

RiceSNP-ABST: a deep learning approach to identify abiotic stress-associated single nucleotide polymorphisms in rice.

Given the adverse effects faced by rice due to abiotic stresses, the precise and rapid identificatio...

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