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Data science in psychiatry

Scheepers, F E ; Menger, V ; Hagoort, K

Tijdschrift voor psychiatrie, 2018, Vol.60 (3), p.205-209

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Título:
Data science in psychiatry
Autor: Scheepers, F E ; Menger, V ; Hagoort, K
Assuntos: Data Collection ; Data Mining - methods ; Datasets as Topic ; Humans ; Precision Medicine ; Psychiatry - trends
É parte de: Tijdschrift voor psychiatrie, 2018, Vol.60 (3), p.205-209
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Descrição: The information society is digitalising at a fast pace. New technology enables the collection of real life and real time information from sources that were inaccessible before. This creates an inordinate amount of dynamic data and, consequently, opportunities to introduce new insights and improvement of treatment in the field of psychiatry. AIM: To clarify the definition of big data and how a big data approach can reform care into a data driven, patient oriented dynamic system which is constantly learning. METHOD: Brief description of a pilot effected at the UMC Utrecht where the Cross Industry Standard Process for Interactive Data Mining (CRISP-IDM) was performed and description of applications in the future. RESULTS: The described approach and examples from literature show that there are possibilities to realise quick improvements in practice and implement new insights from existing data sources. CONCLUSION: Introduction of data science in psychiatric practice offers new prospects.
Editor: Netherlands
Idioma: Holandês

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