Causation in Population Health Informatics and Data Science / by Olaf Dammann, Benjamin Smart.

Format:

Book

Author/Creator:

Dammann, Olaf, author.

Smart, Benjamin, author.

Contributor:

SpringerLink (Online service)

Series:

Medicine (Springer-11650)

Language:

English

Subjects (All):

Medical informatics.

Logic.

Epidemiology.

Health Informatics.

Local Subjects:

Health Informatics.

Logic.

Epidemiology.

Physical Description:

1 online resource (IX, 134 pages) : 15 illustrations, 1 illustrations in color

Edition:

First edition 2019.

Contained In:

Springer eBooks

Place of Publication:

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

System Details:

text file PDF

Summary:

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.

Contents:

Introduction

Data Interpretation

Data Generation

Informatics

Philosophy

Causal inference

Knowledge Integration

Systems Thinking

Summary and conclusion.

Other Format:

Printed edition:

ISBN:

978-3-319-96307-5

9783319963075

Access Restriction:

Restricted for use by site license.