AIMC Topic: Depression

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Continuous Scoring of Depression From EEG Signals via a Hybrid of Convolutional Neural Networks.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Depression score is traditionally determined by taking the Beck depression inventory (BDI) test, which is a qualitative questionnaire. Quantitative scoring of depression has also been achieved by analyzing and classifying pre-recorded electroencephal...

Detection of child depression using machine learning methods.

PloS one
BACKGROUND: Mental health problems, such as depression in children have far-reaching negative effects on child, family and society as whole. It is necessary to identify the reasons that contribute to this mental illness. Detecting the appropriate sig...

Treatment selection using prototyping in latent-space with application to depression treatment.

PloS one
Machine-assisted treatment selection commonly follows one of two paradigms: a fully personalized paradigm which ignores any possible clustering of patients; or a sub-grouping paradigm which ignores personal differences within the identified groups. W...

Mechanisms and Methods to Understand Depressive Symptoms.

Issues in mental health nursing
Depressive symptoms, feelings of sadness, anger, and loss that interfere with a person's daily life, are prevalent health concerns across populations that significantly result in adverse health outcomes with direct and indirect economic burdens at a ...

Using CatBoost algorithm to identify middle-aged and elderly depression, national health and nutrition examination survey 2011-2018.

Psychiatry research
Depression is one of the most common mental health problems in middle-aged and elderly people. The establishment of risk factor-based depression risk assessment model is conducive to early detection and early treatment of high-risk groups of depressi...

Natural language processing for cognitive therapy: Extracting schemas from thought records.

PloS one
The cognitive approach to psychotherapy aims to change patients' maladaptive schemas, that is, overly negative views on themselves, the world, or the future. To obtain awareness of these views, they record their thought processes in situations that c...

Chatbot-Delivered Psychotherapy for Adults With Depressive and Anxiety Symptoms: A Systematic Review and Meta-Regression.

Behavior therapy
Although psychotherapy is a well-established treatment for depression and anxiety, chatbot-delivered psychotherapy is an emerging field that has yet to be explored in depth. This review aims to (a) examine the effectiveness of chatbot-delivered psych...

Machine learning in the prediction of depression treatment outcomes: a systematic review and meta-analysis.

Psychological medicine
BACKGROUND: Multiple treatments are effective for major depressive disorder (MDD), but the outcomes of each treatment vary broadly among individuals. Accurate prediction of outcomes is needed to help select a treatment that is likely to work for a gi...

Artificial neural network and decision tree models of post-stroke depression at 3 months after stroke in patients with BMI ≥ 24.

Journal of psychosomatic research
OBJECTIVE: Previous studies have shown that excess weight (including obesity and overweight) can increase the risk of cardiovascular, cerebrovascular and other diseases, but there is no study on the incidence of post-stroke depression (PSD) and relat...

The effects of a sleep robot intervention on sleep, depression and anxiety in adults with insomnia - Study protocol of a randomized waitlist-controlled trial.

Contemporary clinical trials
Insomnia is a common sleep disorder characterized by difficulties initiating sleep, maintaining sleep and/or early-morning awakenings. Hyperarousal is a common causal and maintaining factor in insomnia models. Different techniques to decrease arousal...