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How data science can advance mental health research
by
John, Ann
, Inkster, Becky
, McIntosh, Andrew M.
, Ibrahim, Zina
, Davis, Katrina A. S.
, Russ, Tom C.
, Stewart, Rob
, Woelbert, Eva
, Lee, William
, Maxwell, Margaret
, Hafferty, Jonathan D.
in
631/114
/ 631/477
/ 692/308
/ Access
/ Application
/ Behavioral Sciences
/ Big Data
/ Biomedical and Life Sciences
/ Biomedical Research
/ Classification
/ Clinical research
/ Computers
/ Data Science
/ Diagnostic tests
/ Disease
/ Disease management
/ Etiology
/ Experimental Psychology
/ Health research
/ Health services
/ Humans
/ Life Sciences
/ Medical diagnosis
/ Medical research
/ Mental disorders
/ Mental Disorders - diagnosis
/ Mental Disorders - etiology
/ Mental Disorders - therapy
/ Mental health
/ Mental health services
/ Microeconomics
/ Neurosciences
/ Personality and Social Psychology
/ Perspective
/ Research applications
/ Science
2019
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How data science can advance mental health research
by
John, Ann
, Inkster, Becky
, McIntosh, Andrew M.
, Ibrahim, Zina
, Davis, Katrina A. S.
, Russ, Tom C.
, Stewart, Rob
, Woelbert, Eva
, Lee, William
, Maxwell, Margaret
, Hafferty, Jonathan D.
in
631/114
/ 631/477
/ 692/308
/ Access
/ Application
/ Behavioral Sciences
/ Big Data
/ Biomedical and Life Sciences
/ Biomedical Research
/ Classification
/ Clinical research
/ Computers
/ Data Science
/ Diagnostic tests
/ Disease
/ Disease management
/ Etiology
/ Experimental Psychology
/ Health research
/ Health services
/ Humans
/ Life Sciences
/ Medical diagnosis
/ Medical research
/ Mental disorders
/ Mental Disorders - diagnosis
/ Mental Disorders - etiology
/ Mental Disorders - therapy
/ Mental health
/ Mental health services
/ Microeconomics
/ Neurosciences
/ Personality and Social Psychology
/ Perspective
/ Research applications
/ Science
2019
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Do you wish to request the book?
How data science can advance mental health research
by
John, Ann
, Inkster, Becky
, McIntosh, Andrew M.
, Ibrahim, Zina
, Davis, Katrina A. S.
, Russ, Tom C.
, Stewart, Rob
, Woelbert, Eva
, Lee, William
, Maxwell, Margaret
, Hafferty, Jonathan D.
in
631/114
/ 631/477
/ 692/308
/ Access
/ Application
/ Behavioral Sciences
/ Big Data
/ Biomedical and Life Sciences
/ Biomedical Research
/ Classification
/ Clinical research
/ Computers
/ Data Science
/ Diagnostic tests
/ Disease
/ Disease management
/ Etiology
/ Experimental Psychology
/ Health research
/ Health services
/ Humans
/ Life Sciences
/ Medical diagnosis
/ Medical research
/ Mental disorders
/ Mental Disorders - diagnosis
/ Mental Disorders - etiology
/ Mental Disorders - therapy
/ Mental health
/ Mental health services
/ Microeconomics
/ Neurosciences
/ Personality and Social Psychology
/ Perspective
/ Research applications
/ Science
2019
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Journal Article
How data science can advance mental health research
2019
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Overview
Accessibility of powerful computers and availability of so-called big data from a variety of sources means that data science approaches are becoming pervasive. However, their application in mental health research is often considered to be at an earlier stage than in other areas despite the complexity of mental health and illness making such a sophisticated approach particularly suitable. In this Perspective, we discuss current and potential applications of data science in mental health research using the UK Clinical Research Collaboration classification: underpinning research; aetiology; detection and diagnosis; treatment development; treatment evaluation; disease management; and health services research. We demonstrate that data science is already being widely applied in mental health research, but there is much more to be done now and in the future. The possibilities for data science in mental health research are substantial.
Russ et al. discuss the broad applications of data science to mental health research and consider future ways that big data can improve detection, diagnosis, treatment, healthcare provision and disease management.
Publisher
Nature Publishing Group UK,Nature Publishing Group
Subject
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