Anxiety & Stress

Key factors selection on adolescents with non-suicidal self-injury: A support vector machine based approach.

Comparing a family structure to a company, one can often think of parents as leaders and adolescents as employees. Stressful family environments and anxiety levels, depression levels, personality disorders, emotional regulation difficulties, and childhood trauma may all contribute to non-suicidal self-injury (NSSI) behaviors. We presented a support vector machine (SVM) based method for discovering...

Intervention with a humanoid robot avatar for individuals with social anxiety disorders comorbid with autism spectrum disorders.

For some individuals with social anxiety disorders (SAD) comorbid with autism spectrum disorders (ASD), it is difficult to speak in front of others. Herein, we report the case of a patient with SAD comorbid with ASD who could not speak in front of others until she used a humanoid robot as her avatar. During the intervention, her personality changed from shy to outgoing, which is explained by the P...

The rise of robots increases job insecurity and maladaptive workplace behaviors: Multimethod evidence.

Robots are transforming the nature of human work. Although human-robot collaborations can create new jobs and increase productivity, pundits often war...

Predicting the evolution trajectory of population-driven connectional brain templates using recurrent multigraph neural networks.

The mapping of the time-dependent evolution of the human brain connectivity using longitudinal and multimodal neuroimaging datasets provides insights ...

Multimodal fusion diagnosis of depression and anxiety based on CNN-LSTM model.

BACKGROUND: In recent years, more and more people suffer from depression and anxiety. These symptoms are hard to be spotted and can be very dangerous....

Computer assisted identification of stress, anxiety, depression (SAD) in students: A state-of-the-art review.

Stress, depression, and anxiety are a person's physiological states that emerge from various body features such as speech, body language, eye contact,...

Deep Learning-Based Attenuation Correction Improves Diagnostic Accuracy of Cardiac SPECT.

To improve diagnostic accuracy, myocardial perfusion imaging (MPI) SPECT studies can use CT-based attenuation correction (AC). However, CT-based AC is...

Enhancing the quality of cognitive behavioral therapy in community mental health through artificial intelligence generated fidelity feedback (Project AFFECT): a study protocol.

BACKGROUND: Each year, millions of Americans receive evidence-based psychotherapies (EBPs) like cognitive behavioral therapy (CBT) for the treatment o...

Predicting Mental Health of Best Human Capital for Sustainable Organization through Psychological and Personality Health Issues: Shift from Traditional to Novel Machine Learning-Supervised Technique Approach.

Researchers in the past discussed the psychological issue like stress, anxiety, depression, phobias on various forms, and cognitive issues (e.g., posi...

Machine-learning as a validated tool to characterize individual differences in free recall of naturalistic events.

The use of naturalistic stimuli, such as narrative movies, is gaining popularity in many fields, characterizing memory, affect, and decision-making. N...

Deep Learning-Based Digital Subtraction Angiography Characteristics in Nursing of Maintenance Hemodialysis Patients.

This study is aimed at exploring the diagnostic value of digital subtraction angiography (DSA) based on faster region-based convolutional networks (Fa...

DetecDiv, a generalist deep-learning platform for automated cell division tracking and survival analysis.

Automating the extraction of meaningful temporal information from sequences of microscopy images represents a major challenge to characterize dynamica...

Predicting social anxiety in young adults with machine learning of resting-state brain functional radiomic features.

Social anxiety is a symptom widely prevalent among young adults, and when present in excess, can lead to maladaptive patterns of social behavior. Rece...

Artificial intelligence uncovers carcinogenic human metabolites.

The genome of a eukaryotic cell is often vulnerable to both intrinsic and extrinsic threats owing to its constant exposure to a myriad of heterogeneou...

A Conditional GAN for Generating Time Series Data for Stress Detection in Wearable Physiological Sensor Data.

Human-centered applications using wearable sensors in combination with machine learning have received a great deal of attention in the last couple of ...

Predicting the Next-Day Perceived and Physiological Stress of Pregnant Women by Using Machine Learning and Explainability: Algorithm Development and Validation.

BACKGROUND: Cognitive behavioral therapy-based interventions are effective in reducing prenatal stress, which can have severe adverse health effects o...

Influences of Edaravone on Necroptosis-Related Proteins and Oxidative Stress in Rats with Lower Extremity Ischemia/Reperfusion Injury.

The study aimed to investigate the influences of edaravone on necroptosis-related proteins and oxidative stress in rats with lower extremity ischemia/...

Predictors of accurate intrapedicular screw placement in single-level lumbar (L4-5) fusion: robot-assisted pedicle screw, traditional pedicle screw, and cortical bone trajectory screw insertion.

BACKGROUND: The superiorities in proximal facet joint protection of robot-assisted (RA) pedicle screw placement and screw implantation via the cortica...

Aberrated Multidimensional EEG Characteristics in Patients with Generalized Anxiety Disorder: A Machine-Learning Based Analysis Framework.

Although increasing evidences support the notion that psychiatric disorders are associated with abnormal communication between brain regions, scattere...

Deep Learning Approach for Detection of Underground Natural Gas Micro-Leakage Using Infrared Thermal Images.

The leakage of underground natural gas has a negative impact on the environment and safety. Trace amounts of gas leak concentration cannot reach the t...