Anxiety & Stress

Artificial intelligence-derived stress ejection fraction in stress cardiac magnetic resonance with dipyridamole: bridging past insights with future innovations.

Artificial intelligence-based fully automated stress left ventricular ejection fraction as a prognostic marker in patients undergoing stress cardiovascular magnetic resonance.

AIMS: This study aimed to determine in patients undergoing stress cardiovascular magnetic resonance ...

RiceSNP-BST: a deep learning framework for predicting biotic stress-associated SNPs in rice.

Rice consistently faces significant threats from biotic stresses, such as fungi, bacteria, pests, an...

Black-White Differences in Chronic Stress Exposures to Predict Preterm Birth: Interpretable, Race/Ethnicity-Specific Machine Learning Models.

We developed Multivariate Adaptive Regression Splines (MARS) machine learning models of chronic stre...

Enhanced Driver Stress Prediction from Multiple Biosignals via CNN Encoder-Decoder Model.

In this work, we present PhysioFuseNet, a novel framework designed to enhance driver stress state cl...

Acute Stress Disorder Detection using Machine Learning based on resting-state fMRI.

Early diagnosis of Acute Stress Disorder (ASD) is important, given its potential progression to post...

Physical, Social and Cognitive Stressor Identification using Electrocardiography-derived Features and Machine Learning from a Wearable Device.

Anxiety is a prevalent and detrimental mental health condition affecting young adults, particularly ...

Differential Private Federated Transfer Learning for Mental Health Monitoring in Everyday Settings: A Case Study on Stress Detection.

Mental health conditions, prevalent across various demographics, necessitate efficient monitoring to...

[Identification of oxidative stress-related biomarkers in chronic rhinosinusitis with nasal polyps using WGCNA combined with machine learning algorithms].

To identify diagnostic markers related to oxidative stress in chronic rhinosinusitis with nasal pol...

Artificial Intelligence on The Couch. Staying Human Post-AI.

This paper examines the human relationship to technology, and AI in particular, including the propos...

Toward personalized care for insomnia in the US Army: a machine learning model to predict response to cognitive behavioral therapy for insomnia.

STUDY OBJECTIVES: The standard of care for military personnel with insomnia is cognitive behavioral ...

Bone Age Prediction under Stress.

Evaluating the Robustness of a Deep Learning Bone Age Algorithm to Clinical Image Variation Using Computational Stress Testing.

Purpose To evaluate the robustness of an award-winning bone age deep learning (DL) model to extensiv...

Surgical stress response in robot-assisted versus laparoscopic surgery for colon cancer (SIRIRALS): randomized clinical trial.

BACKGROUND: Evidence for the routine use of robotic technology and its impact on short-term outcomes...

The League: A person-centred approach to the development of social robotics for paediatric anxiety.

BACKGROUND: Social robots are promising tools to improve the quality of life of children and youth l...

Geriatric depression and anxiety screening via deep learning using activity tracking and sleep data.

BACKGROUND: Geriatric depression and anxiety have been identified as mood disorders commonly associa...

Machine and Deep Learning: Artificial Intelligence Application in Biotic and Abiotic Stress Management in Plants.

Biotic and abiotic stresses significantly affect plant fitness, resulting in a serious loss in food ...

Emulation of a Target Trial to Estimate the Effect of Selective Serotonin Reuptake Inhibitors on the Development of Antimicrobial-Resistant Infections using Electronic Health Record Data and Causal Machine Learning.

Antimicrobial resistance is a significant public health concern. The use of selective serotonin reup...

Integrating AI into Clinical Workflows: A Simulation Study on Implementing AI-aided Same-day Diagnostic Testing Following an Abnormal Screening Mammogram.

Artificial intelligence (AI) shows promise in clinical tasks, yet its integration into workflows rem...

Using Artificial Intelligence to Identify Effective Components of Computer-Assisted Cognitive Behavioural Therapy.

Although clinician-supported computer-assisted cognitive-behaviour therapy (CCBT) is well establishe...

The New Emerging Treatment Choice for Major Depressive Disorders: Digital Therapeutics.

The chapter provides an in-depth analysis of digital therapeutics (DTx) as a revolutionary approach ...