Probabilistic subgroup identification using Bayesian finite mixture modelling: a case study in Parkinson's disease phenotype identification.

Abstract excerpt

This article explores the use of probabilistic classification, namely finite mixture modelling, for identification of complex disease phenotypes, given cross-sectional data. In particular, if focuses on posterior probabilities of subgroup membership, a standard output of finite mixture modelling, and how the quantification of uncertainty in these probabilities can lead to more detailed analyses. Using a Bayesian...

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