AIMC Topic: Mental Disorders

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Drug Repositioning for Schizophrenia and Depression/Anxiety Disorders: A Machine Learning Approach Leveraging Expression Data.

IEEE journal of biomedical and health informatics Jul 16, 2018
Development of new medications is a lengthy and costly process, and drug repositioning might help to shorten the development cycle. We present a machine learning (ML) workflow to drug discovery or repositioning by predicting indication for a particul...
Humans Computational Biology Support Vector Machine Drug Repositioning Machine Learning Mental Disorders
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Active Inference in OpenAI Gym: A Paradigm for Computational Investigations Into Psychiatric Illness.

Biological psychiatry. Cognitive neuroscience and neuroimaging Jul 10, 2018
BACKGROUND: Artificial intelligence has recently attained humanlike performance in a number of gamelike domains. These advances have been spurred by brain-inspired architectures and algorithms such as hierarchical filtering and reinforcement learning...
Neuroimaging Video Games Middle Aged Anhedonia Female Mental Disorders Young Adult Computer Simulation Male Adult Humans Aging Artificial Intelligence
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Making Individual Prognoses in Psychiatry Using Neuroimaging and Machine Learning.

Biological psychiatry. Cognitive neuroscience and neuroimaging Apr 22, 2018
Psychiatric prognosis is a difficult problem. Making a prognosis requires looking far into the future, as opposed to making a diagnosis, which is concerned with the current state. During the follow-up period, many factors will influence the course of...
Humans Psychiatry Prognosis Neuroimaging Machine Learning Mental Disorders
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Machine Learning Approaches for Clinical Psychology and Psychiatry.

Annual review of clinical psychology Jan 29, 2018
Machine learning approaches for clinical psychology and psychiatry explicitly focus on learning statistical functions from multidimensional data sets to make generalizable predictions about individuals. The goal of this review is to provide an access...
Psychology, Clinical Psychiatry Precision Medicine Machine Learning Mental Disorders Humans
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Automatic mining of symptom severity from psychiatric evaluation notes.

International journal of methods in psychiatric research Dec 22, 2017
OBJECTIVES: As electronic mental health records become more widely available, several approaches have been suggested to automatically extract information from free-text narrative aiming to support epidemiological research and clinical decision-making...
Adult Severity of Illness Index Mental Disorders Electronic Health Records Neural Networks, Computer Data Mining Humans Machine Learning
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Machine Learning for Precision Psychiatry: Opportunities and Challenges.

Biological psychiatry. Cognitive neuroscience and neuroimaging Dec 6, 2017
The nature of mental illness remains a conundrum. Traditional disease categories are increasingly suspected to misrepresent the causes underlying mental disturbance. Yet psychiatrists and investigators now have an unprecedented opportunity to benefit...
Precision Medicine Mental Disorders Endophenotypes Psychiatry Humans Machine Learning
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Predicting mental conditions based on "history of present illness" in psychiatric notes with deep neural networks.

Journal of biomedical informatics Jun 10, 2017
BACKGROUND: Applications of natural language processing to mental health notes are not common given the sensitive nature of the associated narratives. The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) changed this scenari...
Natural Language Processing Humans Machine Learning Mental Disorders Neural Networks, Computer
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A hybrid approach to automatic de-identification of psychiatric notes.

Journal of biomedical informatics Jun 7, 2017
De-identification, or identifying and removing protected health information (PHI) from clinical data, is a critical step in making clinical data available for clinical applications and research. This paper presents a natural language processing syste...
Data Anonymization Automation Mental Disorders Natural Language Processing Humans
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Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning.

Annual review of clinical psychology Mar 17, 2017
Sensors in everyday devices, such as our phones, wearables, and computers, leave a stream of digital traces. Personal sensing refers to collecting and analyzing data from sensors embedded in the context of daily life with the aim of identifying human...
Neurophysiological Monitoring Mental Disorders Telemedicine Humans Machine Learning
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Association between abnormal brain functional connectivity in children and psychopathology: A study based on graph theory and machine learning.

The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry Feb 8, 2017
OBJECTIVES: One of the major challenges facing psychiatry is how to incorporate biological measures in the classification of mental health disorders. Many of these disorders affect brain development and its connectivity. In this study, we propose a n...
Cerebral Cortex Connectome Child Development Adolescent Development Humans Support Vector Machine Mental Disorders Adolescent Nerve Net Female Magnetic Resonance Imaging Child Male
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