Titlebook: Causation in Population Health Informatics and Data Science; Olaf Dammann,Benjamin Smart Book 2019 Springer Nature Switzerland AG 2019 Cau

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,Programmieren hei?t, Systeme zu bauen,y domain, we drill down from computer science via health informatics to public health informatics. The analytics domain includes biostatistics, bioinformatics, epidemiology, and simulation. In the conceptual domain, we introduce the philosophy of information, and of health and causation. Taken toget

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https://doi.org/10.1007/978-3-663-10927-3causal inference in medicine and population health informatics. With origins tracing back to at least the eighteenth century, the problem of induction (that is, the problem of justifying inferences from observed data to likely future or unobserved outcomes) is one of the most discussed issues in the

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,Programmieren hei?t, Systeme zu bauen,, we discuss risk estimation, the focus of public health informatics methods. First, we introduce the concepts of risk and prediction. We contrast individual and population risk and discuss why using quantitative risk estimates in individuals is problematic. We describe methods for risk estimation i

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