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Anxiety Disorders

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Deep learning for the prediction of clinical outcomes in internet-delivered CBT for depression and anxiety.

PloS one
In treating depression and anxiety, just over half of all clients respond. Monitoring and obtaining early client feedback can allow for rapidly adapted treatment delivery and improve outcomes. This study seeks to develop a state-of-the-art deep-learn...

Analysis of therapeutic effect of subliminal cognition combined with hypnotherapy on anxiety disorder via neural network.

Biotechnology & genetic engineering reviews
Hypnotherapy combined with cognitive therapy is an effective way to intervene anxiety problems, which also responds to the call that using hypnotherapy to treat somatic disorders should become a trend in the future. This paper constructs an evaluatio...

Virtual and Augmented Simulations in Mental Health.

Current psychiatry reports
PURPOSE OF REVIEW: This examines significant trends and developments in the utilization of virtual reality (VR) and augmented reality (AR) simulations in the field of mental health and education. The objective is to gain insights into the emerging ap...

[Deep Learning-Based Identification of Common Complication Features of Surgical Incisions].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
OBJECTIVE: In recent years, due to the development of accelerated recovery after surgery and day surgery in the field of surgery, the average length-of-stay of patients has been shortened and patients stay at home for post-surgical recovery and heali...

Identifying self-disclosed anxiety on Twitter: A natural language processing approach.

Psychiatry research
BACKGROUND: Text analyses of social media posts are a promising source of mental health information. This study used natural language processing to explore distinct language patterns on Twitter related to self-reported anxiety diagnosis.

Wearable Artificial Intelligence for Detecting Anxiety: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: Anxiety disorders rank among the most prevalent mental disorders worldwide. Anxiety symptoms are typically evaluated using self-assessment surveys or interview-based assessment methods conducted by clinicians, which can be subjective, tim...

Geriatric depression and anxiety screening via deep learning using activity tracking and sleep data.

International journal of geriatric psychiatry
BACKGROUND: Geriatric depression and anxiety have been identified as mood disorders commonly associated with the onset of dementia. Currently, the diagnosis of geriatric depression and anxiety relies on self-reported assessments for primary screening...

Personality traits as predictors of depression across the lifespan.

Journal of affective disorders
BACKGROUND: Depression is a major public health concern. A barrier for research has been the heterogeneous nature of depression, complicated by the categorical diagnosis of depression which is based on a cluster of symptoms, each with its own etiolog...

Unraveling the distinction between depression and anxiety: A machine learning exploration of causal relationships.

Computers in biology and medicine
OBJECTIVE: Depression and anxiety, prevalent coexisting mood disorders, pose a clinical challenge in accurate differentiation, hindering effective healthcare interventions. This research addressed this gap by employing a streamlined Symptom Checklist...

Predicting post-treatment symptom severity for adults receiving psychological therapy in routine care for generalised anxiety disorder: a machine learning approach.

Psychiatry research
Approximately half of generalised anxiety disorder (GAD) patients do not recover from first-line treatments, and no validated prediction models exist to inform individuals or clinicians of potential treatment benefits. This study aimed to develop and...