AIMC Topic: Mental Disorders

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Detection of Types of Mental Illness through the Social Network Using Ensembled Deep Learning Model.

Computational intelligence and neuroscience Mar 26, 2022
In today's era, social networking platforms are widely used to share emotions. These types of emotions are often analyzed to predict the user's behavior. In this paper, these types of sentiments are classified to predict the mental illness of the use...
Humans Neural Networks, Computer Mental Disorders Deep Learning Social Networking
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Commentary to "Translational machine learning for child and adolescent psychiatry".

Journal of child psychology and psychiatry, and allied disciplines Mar 7, 2022
In this commentary on 'Translational Machine Learning for Child and Adolescent Psychiatry,' by Dwyer and Koutsouleris, we summarize some of the main points made by the authors, which highlight the importance of emerging applications of machine learni...
Humans Artificial Intelligence Machine Learning Mental Disorders Child Adolescent Family Adolescent Psychiatry
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Significance and stability of deep learning-based identification of subtypes within major psychiatric disorders.

Molecular psychiatry Feb 28, 2022
Deep Learning Humans Neural Networks, Computer Mental Disorders
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Comparing Deep Learning and Conventional Machine Learning Models for Predicting Mental Illness from History of Present Illness Notations.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 21, 2022
Mental illness, a serious problem across the globe, requires multi-pronged solutions including effective computational models to predict illness. Mental illness diagnosis is complicated by the pronounced sharing of symptoms and mutual pre-disposition...
Mental Disorders Humans Deep Learning Machine Learning
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AI ethics in computational psychiatry: From the neuroscience of consciousness to the ethics of consciousness.

Behavioural brain research Dec 4, 2021
Methods used in artificial intelligence (AI) overlap with methods used in computational psychiatry (CP). Hence, considerations from AI ethics are also relevant to ethical discussions of CP. Ethical issues include, among others, fairness and data owne...
Humans Neurosciences Psychiatry Deep Learning Consciousness Artificial Intelligence Mental Disorders
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Differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study.

Scientific reports Oct 29, 2021
The placebo effect across psychiatric disorders is still not well understood. In the present study, we conducted meta-analyses including meta-regression, and machine learning analyses to investigate whether the power of placebo effect depends on the ...
Male Middle Aged Case-Control Studies Aged Young Adult Adult Psychotropic Drugs Placebo Effect Adolescent Child Clinical Trials as Topic Humans Machine Learning Mental Disorders Female
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Year 2020 (with COVID): Observation of Scientific Literature on Clinical Natural Language Processing.

Yearbook of medical informatics Sep 3, 2021
OBJECTIVES: To analyze the content of publications within the medical NLP domain in 2020.
Natural Language Processing Clinical Trials as Topic Medical Records Humans Social Networking COVID-19 Mental Disorders
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Deep graph neural network-based prediction of acute suicidal ideation in young adults.

Scientific reports Aug 4, 2021
Precise remote evaluation of both suicide risk and psychiatric disorders is critical for suicide prevention as well as for psychiatric well-being. Using questionnaires is an alternative to labor-intensive diagnostic interviews in a large general popu...
Area Under Curve Self Concept Surveys and Questionnaires Adolescent Suicidal Ideation Depression Resilience, Psychological Humans Neural Networks, Computer Adult Sensitivity and Specificity Male Anxiety Suicide, Attempted Psychiatric Status Rating Scales Female Risk Factors Young Adult Mental Disorders Prognosis Republic of Korea
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Explainable deep learning predictions for illness risk of mental disorders in Nanjing, China.

Environmental research Jul 28, 2021
Epidemiological studies have revealed the associations of air pollutants and meteorological factors with a range of mental health conditions. However, little is known about local explanations and global understanding on the importance and effect of i...
Mental Disorders Deep Learning China Air Pollutants Humans Air Pollution Particulate Matter
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Explaining distortions in metacognition with an attractor network model of decision uncertainty.

PLoS computational biology Jul 26, 2021
Metacognition is the ability to reflect on, and evaluate, our cognition and behaviour. Distortions in metacognition are common in mental health disorders, though the neural underpinnings of such dysfunction are unknown. One reason for this is that mo...
Uncertainty Metacognition Linear Models Models, Psychological Judgment Decision Making Mental Disorders Bias Humans Computational Biology Psychomotor Performance Neural Networks, Computer Models, Neurological
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