AIMC Topic: Anxiety
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Identifying the presence and timing of discrete mood states prior to therapy.
Behaviour research and therapy
Feb 27, 2020
The present study tested a novel, person-specific method for identifying discrete mood profiles from time-series data, and examined the degree to which these profiles could be predicted by lagged mood and anxiety variables and time-based variables, i...
Anxiety
Anxiety Disorders
Depression
Latent Class Analysis
Time Factors
Adult
Male
Middle Aged
Depressive Disorder, Major
Humans
Hope
Machine Learning
Anger
Female
Avoidance Learning
Young Adult
Rumination, Cognitive
Irritable Mood
Psychotherapy
Affect
Anhedonia
Fear
Biological Variation, Individual
Artificial neural networks for predicting social comparison effects among female Instagram users.
PloS one
Feb 25, 2020
Systematic exposure to social media causes social comparisons, especially among women who compare their image to others; they are particularly vulnerable to mood decrease, self-objectification, body concerns, and lower perception of themselves. This ...
Prognostic factors of Rapid symptoms progression in patients with newly diagnosed parkinson's disease.
Artificial intelligence in medicine
Jan 21, 2020
Tracking symptoms progression in the early stages of Parkinson's disease (PD) is a laborious endeavor as the disease can be expressed with vastly different phenotypes, forcing clinicians to follow a multi-parametric approach in patient evaluation, lo...
An Investigation of Various Machine and Deep Learning Techniques Applied in Automatic Fear Level Detection and Acrophobia Virtual Therapy.
Sensors (Basel, Switzerland)
Jan 15, 2020
In this paper, we investigate various machine learning classifiers used in our Virtual Reality (VR) system for treating acrophobia. The system automatically estimates fear level based on multimodal sensory data and a self-reported emotion assessment....
Could a rising robot workforce make humans less prejudiced?
The American psychologist
Jan 9, 2020
Automation is becoming ever more prevalent, with robot workers replacing many human employees. Many perspectives have examined the economic impact of a robot workforce, but here we consider its social impact: How will the rise of robot workers affect...
The diagnosticity of psychophysiological signatures: Can we disentangle mental workload from acute stress with ECG and fNIRS?
International journal of psychophysiology : official journal of the International Organization of Psychophysiology
Oct 19, 2019
The ability to identify reliable and sensitive physiological signatures of psychological dimensions is key to developing intelligent adaptive systems that may in turn help to mitigate human error in complex operations. The challenge of this endeavor ...
Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis.
Human brain mapping
Oct 1, 2019
Previous structural and functional neuroimaging studies have implicated distributed brain regions and networks in depression. However, there are no robust imaging biomarkers that are specific to depression, which may be due to clinical heterogeneity ...
Comparing blind spots of unsedated ultrafine, sedated, and unsedated conventional gastroscopy with and without artificial intelligence: a prospective, single-blind, 3-parallel-group, randomized, single-center trial.
Gastrointestinal endoscopy
Sep 18, 2019
BACKGROUND AND AIMS: EGD is the most vital procedure for the diagnosis of upper GI lesions. We aimed to compare the performance of unsedated ultrathin transoral endoscopy (U-TOE), unsedated conventional EGD (C-EGD), and sedated C-EGD with or without ...
Machine Learning to Understand the Immune-Inflammatory Pathways in Fibromyalgia.
International journal of molecular sciences
Aug 29, 2019
Fibromyalgia (FM) is a chronic syndrome characterized by widespread musculoskeletal pain, and physical and emotional symptoms. Although its pathophysiology is largely unknown, immune-inflammatory pathways may be involved. We examined serum interleuki...
Toward Robust Anxiety Biomarkers: A Machine Learning Approach in a Large-Scale Sample.
Biological psychiatry. Cognitive neuroscience and neuroimaging
Jun 21, 2019
BACKGROUND: The field of psychiatry has long sought biomarkers that can objectively diagnose patients, predict treatment response, or identify individuals at risk of illness onset. However, reliable psychiatric biomarkers have yet to emerge. The rece...
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