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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