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Causation in Population Health Infor...
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Causation in Population Health Informatics and Data Science
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Causation in Population Health Informatics and Data Science/ by Olaf Dammann, Benjamin Smart.
Author:
Dammann, Olaf.
other author:
Smart, Benjamin.
Description:
IX, 134 p. 15 illus., 1 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Health informatics. -
Online resource:
https://doi.org/10.1007/978-3-319-96307-5
ISBN:
9783319963075
Causation in Population Health Informatics and Data Science
Dammann, Olaf.
Causation in Population Health Informatics and Data Science
[electronic resource] /by Olaf Dammann, Benjamin Smart. - 1st ed. 2019. - IX, 134 p. 15 illus., 1 illus. in color.online resource.
Introduction -- Data Interpretation -- Data Generation -- Informatics -- Philosophy -- Causal inference -- Knowledge Integration -- Systems Thinking -- Summary and conclusion.
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.
ISBN: 9783319963075
Standard No.: 10.1007/978-3-319-96307-5doiSubjects--Topical Terms:
1064466
Health informatics.
LC Class. No.: R858-859.7
Dewey Class. No.: 502.85
Causation in Population Health Informatics and Data Science
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Introduction -- Data Interpretation -- Data Generation -- Informatics -- Philosophy -- Causal inference -- Knowledge Integration -- Systems Thinking -- Summary and conclusion.
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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.
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