TY  - BOOK
AU  - Kubben,Pieter
AU  - Dumontier,Michel
AU  - Dekker,Andre
ED  - SpringerLink (Online service)
TI  - Fundamentals of Clinical Data Science
SN  - 9783319997131
AV  - R858-859.7 
U1  - 502.85 23
PY  - 2019///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Health informatics
KW  - Bioinformatics
KW  - Health Informatics
KW  - Computational Biology/Bioinformatics
N1  - Data sources -- Data at scale -- Standards in healthcare data -- Using FAIR data / data stewardship -- Privacy / deidentification -- Preparing your data -- Creating a predictive model -- Diving deeper into models -- Validation and Evaluation of reported models -- Clinical decision support systems -- Mobile app development -- Operational excellence -- Value Based Healthcare (Regulatory concerns); Open Access
N2  - 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
UR  - https://doi.org/10.1007/978-3-319-99713-1
ER  -