Incorporating spontaneous reporting system data to aid causal inference in longitudinal healthcare data
Reps, Jenna M. and Aickelin, Uwe (2014) Incorporating spontaneous reporting system data to aid causal inference in longitudinal healthcare data. In: IEEE International Conference on Data Mining: The Fifth Workshop on Biological Data Mining and its Applications in Healthcare (BioDM 2014), 14 Dec 2014, Shenzhen, China.
Inferring causality using longitudinal observational databases is challenging due to the passive way the data are collected. The majority of associations found within longitudinal observational data are often non-causal and occur due to confounding.
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