Anxiety & Stress

Anxiety in aquatics: Leveraging machine learning models to predict adult zebrafish behavior.

Accurate analysis of anxiety behaviors in animal models is pivotal for advancing neuroscience research and drug discovery. This study compares the potential of DeepLabCut, ZebraLab, and machine learning models to analyze anxiety-related behaviors in adult zebrafish. Using a dataset comprising video recordings of unstressed and pre-stressed zebrafish, we extracted features such as total inactivity ...

Machine learning-assisted implantable plant electrophysiology microneedle sensor for plant stress monitoring.

Plant electrical signals serve as a medium for long-distance signal transmission and are intricately linked to plant stress responses. High-fidelity acquisition and analysis of plant electrophysiological signals contribute to early stress identification, thereby enhancing agricultural production efficiency. While traditional plant electrophysiology monitoring methods like gel electrodes can captur...

Photoplethysmography as a noninvasive surrogate for microneurography in measuring stress-induced sympathetic nervous activation - A machine learning approach.

The sympathetic nervous system (SNS) is essential for the body's immediate response to stress, initiating physiological changes that can be measured t...

Screening for Depression and Anxiety Using a Nonverbal Working Memory Task in a Sample of Older Brazilians: Observational Study of Preliminary Artificial Intelligence Model Transferability.

BACKGROUND: Anxiety and depression represent prevalent yet frequently undetected mental health concerns within the older population. The challenge of ...

Release of complex imaging reports to patients, do radiologists trust AI to help?

BACKGROUND: As a result of the 21st Century Cures Act, radiology reports are immediately released to patients. However, these reports are often too co...

Spectrum of errors in nodule detection and characterization using machine learning: A pictorial essay.

In academic and research settings, computer-aided nodule detection software has been shown to increase accuracy, efficiency, and throughput. However, ...

An explainable predictive model for anxiety symptoms risk among Chinese older adults with abdominal obesity using a machine learning and SHapley Additive exPlanations approach.

BACKGROUND: Early detection of anxiety symptoms can support early intervention and may help reduce the burden of disease in later life in the elderly ...

Screening social anxiety with the Social Artificial Intelligence Picture System.

Social anxiety disorder (SAD) is a prevalent anxiety disorder marked by strong fear and avoidance of social scenarios. Early detection of SAD lays the...

A pilot evaluation of school-based LEGO® robotics therapy for autistic students.

There is emerging evidence that LEGO® therapy is an effective way of supporting younger autistic children develop their communication and social skill...

Understanding veterinary practitioners' responses to adverse events using a combined grounded theory and netnographic natural language processing approach.

Support that mitigates the detrimental impact of adverse events on human healthcare practitioners is underpinned by an understanding of their experien...

Effective feature selection based HOBS pruned- ELM model for tomato plant leaf disease classification.

Tomato cultivation is expanding rapidly, but the tomato sector faces significant challenges from various sources, including environmental (abiotic str...

Research hotspots and trends of neuroimaging in social anxiety: a CiteSpace bibliometric analysis based on Web of Science and Scopus database.

BACKGROUND: This study focused on the research hotspots and development trends of the neuroimaging of social anxiety (SA) in the past 25 years.

Strategies for creation of data reserve and stress testing of medical AI products.

With the fast development of artificial intelligence (AI) and its applications in medicine, it is often said that the time for intelligent medicine is...

Research on mood monitoring and intervention for anxiety disorder patients based on deep learning wearable devices.

BackgroundAnxiety disorders are common mental health issues that have a significant effect on people's quality of life. Conventional techniques for tr...

Smart agriculture: utilizing machine learning and deep learning for drought stress identification in crops.

Plant stress reduction research has advanced significantly with the use of Artificial Intelligence (AI) techniques, such as machine learning and deep ...

Exploring new scientific innovations in combating suicide: a stress detection wristband.

There is a silent pandemic of suicides around the world, with an exponential increase in suicidality and chronic suicidal ideations. The exact global ...

The relationship between artificial intelligence anxiety and unemployment anxiety among university students.

BackgroundThe idea that people will lose their jobs because of robots with artificial intelligence is one of the biggest recent concerns about artific...

Classifying vocal responses of broilers to environmental stressors via artificial neural network.

Detecting early-stage stress in broiler farms is crucial for optimising growth rates and animal well-being. This study aims to classify various stress...

A digital phenotyping dataset for impending panic symptoms: a prospective longitudinal study.

This study investigated the utilization of digital phenotypes and machine learning algorithms to predict impending panic symptoms in patients with moo...

Comparison of machine learning methods for Predicting 3-Year survival in elderly esophageal squamous cancer patients based on oxidative stress.

BACKGROUND: Oxidative stress process plays a key role in aging and cancer; however, currently, there is paucity of machine-learning model studies inve...