1st ed. 2019 edition
by Pieter Kubben (Editor), Michel Dumontier (Editor), Andre Dekker (Editor)
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.
