AIMC Topic: Anxiety
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Detecting the impact of diagnostic procedures in Pap-positive women on anxiety using artificial neural networks.
PloS one
Oct 31, 2024
INTRODUCTION: Women who receive a result of an abnormal Papanicolaou (Pap) smear can fail to participate in follow up procedures, and this is often due to anxiety. This study aimed to apply artificial neural networks (ANN) in prediction of anxiety in...
Prediction of Suicidal Thoughts and Suicide Attempts in People Who Gamble Based on Biological-Psychological-Social Variables: A Machine Learning Study.
The Psychiatric quarterly
Oct 28, 2024
Recent research has shown that people who gamble are more likely to have suicidal thoughts and attempts compared to the general population. Despite the advancements made, no study to date has predicted suicide risk factors in people who gamble using ...
Evaluation of neonatal nurses' anxiety and readiness levels towards the use of artificial intelligence.
Journal of pediatric nursing
Oct 18, 2024
OBJECTIVEC: This is a cross-sectional and descriptive study to determine the levels of artificial intelligence anxiety and readiness of neonatal nurses.
Machine learning for anxiety and depression profiling and risk assessment in the aftermath of an emergency.
Artificial intelligence in medicine
Sep 29, 2024
BACKGROUND & OBJECTIVES: Mental health disorders pose an increasing public health challenge worsened by the COVID-19 pandemic. The pandemic highlighted gaps in preparedness, emphasizing the need for early identification of at-risk groups and targeted...
Relationship matters: Using machine learning methods to predict the mental health severity of Chinese college freshmen during the pandemic period.
Journal of affective disorders
Sep 26, 2024
BACKGROUND: Pandemics act as stressors and may lead to frequent mental health disorders. College student, especially freshmen, are particularly susceptible to experiencing intense mental stress reactions during a pandemic. We aimed to identify stable...
Deep learning dives: Predicting anxiety in zebrafish through novel tank assay analysis.
Physiology & behavior
Sep 16, 2024
Behavior is fundamental to neuroscience research, providing insights into the mechanisms underlying thoughts, actions and responses. Various model organisms, including mice, flies, and fish, are employed to understand these mechanisms. Zebrafish, in ...
Prediction of depressive symptoms severity based on sleep quality, anxiety, and gray matter volume: a generalizable machine learning approach across three datasets.
EBioMedicine
Sep 9, 2024
BACKGROUND: Depressive symptoms are rising in the general population, but their associated factors are unclear. Although the link between sleep disturbances and depressive symptoms severity (DSS) is reported, the predictive role of sleep on DSS and t...
Social anxiety prediction based on ERP features: A deep learning approach.
Journal of affective disorders
Sep 3, 2024
BACKGROUND: Social Anxiety Disorder is traditionally diagnosed using subjective scales that may lack accuracy. Recently, EEG technology has gained importance for anxiety detection due to its ability to capture stable and objective neurophysiological ...
Examining worry and secondary stressors on grief severity using machine learning.
Anxiety, stress, and coping
Aug 21, 2024
BACKGROUND & OBJECTIVES: Worry and loss-related secondary stressors appear to be important correlates of problematic grief responses. However, the relative importance of these variables in the context of established correlates of grief responding, ra...
Self-Administered Interventions Based on Natural Language Processing Models for Reducing Depressive and Anxiety Symptoms: Systematic Review and Meta-Analysis.
JMIR mental health
Aug 21, 2024
BACKGROUND: The introduction of natural language processing (NLP) technologies has significantly enhanced the potential of self-administered interventions for treating anxiety and depression by improving human-computer interactions. Although these ad...
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