Causation in Population Health Informatics and Data Science

Description

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. Front Matter ....Pages i-ix Introduction (Olaf Dammann, Benjamin Smart)....Pages 1-14 Health Data Science (Olaf Dammann, Benjamin Smart)....Pages 15-26 The Metaphysics of Illness Causation (Olaf Dammann, Benjamin Smart)....Pages 27-41 Causal Inference in Population Health Informatics (Olaf Dammann, Benjamin Smart)....Pages 43-61 Making Population Health Knowledge (Olaf Dammann, Benjamin Smart)....Pages 63-77 Population Risk (Olaf Dammann, Benjamin Smart)....Pages 79-98 Integrating Evidence (Olaf Dammann, Benjamin Smart)....Pages 99-115 Conclusion and Invite (Olaf Dammann, Benjamin Smart)....Pages 117-118 Back Matter ....Pages 119-134