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Causation in Population Health Informatics and Data Science

Causation in Population Health Informatics and Data Science

Olaf Dammann, Benjamin Smart
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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.

Catégories:
Année:
2019
Edition:
1st ed.
Editeur::
Springer International Publishing
Langue:
english
ISBN 10:
3319963074
ISBN 13:
9783319963075
Fichier:
PDF, 1.45 MB
IPFS:
CID , CID Blake2b
english, 2019
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