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Fundamentals of Clinical Data Science

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Author: Search for this author SpringerLink (Online service)
Medium identifier: OA
Year: 2019.
Publisher: Cham :, Springer International Publishing :
Media group: eBook
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This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.

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Details

Author: Search for this author SpringerLink (Online service)
Statement of Responsibility: edited by Pieter Kubben, Michel Dumontier, Andre Dekker.
Medium identifier: OA
Year: 2019.
Publisher: Cham :, Springer International Publishing :
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Subject type: Search for this subject type MBG, MED000000, UB
ISBN: 9783319997131
Description: 1st ed. 2019., VIII, 219 p. 45 illus., 35 illus. in color., online resource.
Tags: Health informatics.; Bioinformatics.; Health Informatics.; Computational Biology/Bioinformatics.
Media group: eBook