Causation in Population Health Informatics and Data Science

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.

Platform:

OvidSP

Product Type:

Book

Author:

Dammann, Olaf; Smart, Benjamin

ISBN:

978-3-31-996306-8

Specialty:

• Community Health & Disease Prevention
• Epidemiology
• Health Policy
• Health Systems & Services

Language:

English

Edition:

1st Ed.

Pages:

134

Publication Year:

2018

• Springer Nature Doody's Core Title Collection 2020
• Springer Nature Public Health Book Collection