Causation in population health informatics and data science
著者
書誌事項
Causation in population health informatics and data science
Springer, c2019
大学図書館所蔵 全1件
注記
Includes bibliographical references and index
内容説明・目次
内容説明
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.
目次
Introduction.- Data Interpretation.- Data Generation.- Informatics.- Philosophy.- Causal inference.- Knowledge Integration.- Systems Thinking.- Summary and conclusion.
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