AIMC Topic: Anxiety Disorders
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Prevalence of and factors related to anxiety and depression symptoms among married patients with gynecological malignancies in China.
Asian journal of psychiatry
Aug 18, 2018
OBJECTIVE: This study aims to investigate the prevalence of anxiety and depression among married patients with gynecological malignancies in China and then explores factors related to anxiety and depression.
Predicting suicidal ideation in primary care: An approach to identify easily assessable key variables.
General hospital psychiatry
Feb 2, 2018
OBJECTIVE: To obtain predictors of suicidal ideation, which can also be used for an indirect assessment of suicidal ideation (SI). To create a classifier for SI based on variables of the Patient Health Questionnaire (PHQ) and sociodemographic variabl...
A Trust Model for Ubiquitous Healthcare Environment on the Basis of Adaptable Fuzzy-Probabilistic Inference System.
IEEE journal of biomedical and health informatics
Jul 28, 2017
Trust is considered to be a determinant on psychologist selection which can ensure patient satisfaction. Hence, trust concept is essential to be introduced into ubiquitous healthcare (UH) environment oriented on patients with anxiety disorders. This ...
Separating generalized anxiety disorder from major depression using clinical, hormonal, and structural MRI data: A multimodal machine learning study.
Brain and behavior
Feb 12, 2017
BACKGROUND: Generalized anxiety disorder (GAD) is difficult to recognize and hard to separate from major depression (MD) in clinical settings. Biomarkers might support diagnostic decisions. This study used machine learning on multimodal biobehavioral...
Quantifying Risk for Anxiety Disorders in Preschool Children: A Machine Learning Approach.
PloS one
Nov 23, 2016
Early childhood anxiety disorders are common, impairing, and predictive of anxiety and mood disorders later in childhood. Epidemiological studies over the last decade find that the prevalence of impairing anxiety disorders in preschool children range...
Advanced literature analysis in a Big Data world.
Annals of the New York Academy of Sciences
Nov 10, 2016
Comprehensive data mining of the scientific literature has become an increasing challenge. To address this challenge, Elsevier's Pathway Studio software uses the techniques of natural language processing to systematically extract specific biological ...
National Institute of Mental Health (U.S.)
Database Management Systems
Databases, Bibliographic
Translational Research, Biomedical
Schizophrenia
Data Mining
Abstracting and Indexing
Humans
United States
Animals
Software
Mass Screening
Depressive Disorder, Major
Natural Language Processing
Mental Disorders
Anxiety Disorders
Periodicals as Topic
Biomarkers
Bipolar Disorder
Prognosis
Computational Biology
Biomedical Research
Predicting long-term outcome of Internet-delivered cognitive behavior therapy for social anxiety disorder using fMRI and support vector machine learning.
Translational psychiatry
Mar 17, 2015
Cognitive behavior therapy (CBT) is an effective treatment for social anxiety disorder (SAD), but many patients do not respond sufficiently and a substantial proportion relapse after treatment has ended. Predicting an individual's long-term clinical ...
Recognition of anxiety and depression using gait data recorded by the kinect sensor: a machine learning approach with data augmentation.
Scientific reports
Jul 2, 2025
Anxiety and depression disorders are increasingly common, necessitating methods for real-time assessment and early identification. This study investigates gait analysis as a potential indicator of mental health, using the Microsoft Kinect sensor to c...
Anxiety disorder identification with biomarker detection through subspace-enhanced hypergraph neural network.
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
In this study, we propose a subspace-enhanced hypergraph neural network (seHGNN) for classifying anxiety disorders (AD), which are prevalent mental illnesses that affect a significant portion of the global population. Our seHGNN model utilizes a lear...
Concise multi-class anxiety disorder risk assessment: A novel advanced machine learning approach.
Journal of anxiety disorders
Jun 1, 2025
Rapidly assessing anxiety disorder risk is crucial for effective mental health screen and intervention. However, traditional survey tools such as DASS-42 are time-consuming in responding and scoring. We used a novel advanced machine learning approach...
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