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dc.contributor.editorKubben, Pieter
dc.contributor.editorDumontier, Michel
dc.contributor.editorDekker, Andre
dc.date.accessioned2020-03-18 13:36:15
dc.date.accessioned2020-04-01T08:56:21Z
dc.date.available2020-04-01T08:56:21Z
dc.date.issued2019
dc.identifier1007243
dc.identifier.urihttp://library.oapen.org/handle/20.500.12657/22918
dc.description.abstractThis 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.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBG Medical equipment and techniquesen_US
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issuesen_US
dc.subject.otherMedicine
dc.subject.otherHealth informatics
dc.subject.otherBioinformatics
dc.titleFundamentals of Clinical Data Science
dc.typebook
oapen.identifier.doi10.1007/978-3-319-99713-1
oapen.relation.isPublishedBy6c6992af-b843-4f46-859c-f6e9998e40d5
oapen.pages219
oapen.place.publicationCham


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