Causation in Population Health Informatics and Data Science

Causation in Population Health Informatics and Data Science

Author
Olaf Dammann, Benjamin Smart
Publisher
Springer International Publishing
Language
English
Edition
1st ed.
Year
2019
Page
IX, 134
ISBN
978-3-319-96306-8,978-3-319-96307-5
File Type
pdf
File Size
1.5 MiB

Marketing text: This book covers the overlap between informatics, computer science, philosophy of causation, and causal inference in epidemiology and population health research. Key concepts covered include how data are generated and interpreted, and how and why concepts in health informatics and the philosophy of science should be integrated in a systems-thinking approach. Furthermore, a formal epistemology for the health sciences and public health is suggested.
Causation in Population Health Informatics and Data Science provides a detailed guide of the latest thinking on causal inference in population health informatics. It is therefore a critical resource for all informaticians and epidemiologists interested in the potential benefits of utilising a systems-based approach to causal inference in health informatics.

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