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Book/Printed Material Fundamentals of Clinical Data Science

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About this Item

Title

  • Fundamentals of Clinical Data Science

Summary

  • 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.

Names

  • Dekker, Andre, editor.
  • Dumontier, Michel, editor.
  • Kubben, Pieter, editor.

Created / Published

  • Cham : Springer International Publishing : Imprint: Springer, 2019.

Contents

  • 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).

Headings

  • -  Bioinformatics
  • -  Health informatics
  • -  Health Informatics
  • -  Computational Biology/Bioinformatics

Notes

  • -  Description based on publisher-supplied MARC data.
  • -  Medicine (R0) (SpringerNature-43714)
  • -  Medicine (SpringerNature-11650)

Medium

  • 1 online resource (VIII, 219 pages 45 illustrations, 35 illustrations in color.)

Digital Id

Library of Congress Control Number

  • 2019763156

Rights Advisory

Access Advisory

  • Unrestricted online access
  • Open Access

Online Format

  • image
  • epub

Additional Metadata Formats

Rights & Access

The books in this collection are licensed under open access licenses allowing for the reuse and distribution of each book following the terms described in each license. Researchers should consult the Rights Advisory statement for each title and the accompanying license details for information about rights and permissions associated with each of the licenses.

More about Copyright and other Restrictions.

Cite This Item

Citations are generated automatically from bibliographic data as a convenience, and may not be complete or accurate.

Chicago citation style:

Dekker, Andreitor, Michelitor Dumontier, and Pieteritor Kubben, editor. Fundamentals of Clinical Data Science. Cham: Springer International Publishing: Imprint: Springer, 2019. Image. https://www.loc.gov/item/2019763156/.

APA citation style:

Dekker, A., Dumontier, M. & Kubben, P., editor. (2019) Fundamentals of Clinical Data Science. Cham: Springer International Publishing: Imprint: Springer. [Image] Retrieved from the Library of Congress, https://www.loc.gov/item/2019763156/.

MLA citation style:

Dekker, Andreitor, Michelitor Dumontier, and Pieteritor Kubben, editor. Fundamentals of Clinical Data Science. Cham: Springer International Publishing: Imprint: Springer, 2019. Image. Retrieved from the Library of Congress, <www.loc.gov/item/2019763156/>.