Fundamentals of Clinical Data Science (Hardcover, 1st ed. 2019)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Release date:	2019
First published:	2019
Editors:	Pieter Kubben • Michel Dumontier • Andre Dekker
Dimensions:	235 x 155 x 11mm (L x W x T)
Format:	Hardcover
Pages:	219
Edition:	1st ed. 2019
ISBN-13:	978-3-319-99712-4
Categories:	Books > Medicine > General issues > Medical equipment & techniques > General Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > General
LSN:	3-319-99712-2
Barcode:	9783319997124

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