AIMC Topic: Mental Health
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Digital Data Sources and Their Impact on People's Health: A Systematic Review of Systematic Reviews.
Frontiers in public health
May 5, 2021
Digital data sources have become ubiquitous in modern culture in the era of digital technology but often tend to be under-researched because of restricted access to data sources due to fragmentation, privacy issues, or industry ownership, and the me...
Machine Learning and Natural Language Processing in Mental Health: Systematic Review.
Journal of medical Internet research
May 4, 2021
BACKGROUND: Machine learning systems are part of the field of artificial intelligence that automatically learn models from data to make better decisions. Natural language processing (NLP), by using corpora and learning approaches, provides good perfo...
Emotions of COVID-19: Content Analysis of Self-Reported Information Using Artificial Intelligence.
Journal of medical Internet research
Apr 30, 2021
BACKGROUND: The COVID-19 pandemic has disrupted human societies around the world. This public health emergency was followed by a significant loss of human life; the ensuing social restrictions led to loss of employment, lack of interactions, and burg...
Text mining occupations from the mental health electronic health record: a natural language processing approach using records from the Clinical Record Interactive Search (CRIS) platform in south London, UK.
BMJ open
Mar 25, 2021
OBJECTIVES: We set out to develop, evaluate and implement a novel application using natural language processing to text mine occupations from the free-text of psychiatric clinical notes.
Predicting Emotional States Using Behavioral Markers Derived From Passively Sensed Data: Data-Driven Machine Learning Approach.
JMIR mHealth and uHealth
Mar 22, 2021
BACKGROUND: Mental health disorders affect multiple aspects of patients' lives, including mood, cognition, and behavior. eHealth and mobile health (mHealth) technologies enable rich sets of information to be collected noninvasively, representing a pr...
Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom.
Biological psychiatry. Cognitive neuroscience and neuroimaging
Feb 8, 2021
Artificial intelligence (AI) is increasingly employed in health care fields such as oncology, radiology, and dermatology. However, the use of AI in mental health care and neurobiological research has been modest. Given the high morbidity and mortalit...
Analyzing Description, User Understanding and Expectations of AI in Mobile Health Applications.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Previous research has studied medical professionals' perception of artificial intelligence (AI). However, there has been a limited understanding of how healthcare consumers perceive and use AI-powered technologies such as mobile health apps. We colle...
Conversational Agents for Chronic Disease Self-Management: A Systematic Review.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
We conducted a systematic literature review to assess how conversational agents have been used to facilitate chronic disease self-management. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework was used. Literatu...
A natural language processing approach for identifying temporal disease onset information from mental healthcare text.
Scientific reports
Jan 12, 2021
Receiving timely and appropriate treatment is crucial for better health outcomes, and research on the contribution of specific variables is essential. In the mental health domain, an important research variable is the date of psychosis symptom onset,...
Artificial Intelligence, Social Media and Depression. A New Concept of Health-Related Digital Autonomy.
The American journal of bioethics : AJOB
Jan 4, 2021
The development of artificial intelligence (AI) in medicine raises fundamental ethical issues. As one example, AI systems in the field of mental health successfully detect signs of mental disorders, such as depression, by using data from social media...
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