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

Dekker, Andre(Edited by)Dumontier, Michel(Edited by)Kubben, Pieter(Edited by)
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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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£2.99
Product Details
Springer
3319997130 / 9783319997131
eBook (Adobe Pdf, EPUB)
610.285
21/12/2018
English
219 pages
Copy: 100%; print: 100%