A framework for expert-driven subpopulation discovery and evaluation using subspace clustering for epidemiological data

The present version of DIVA considers a single wave of the cohort data, ignoring the evolution of the population during the horizon of the study. Hence, subspace and subpopulation discovery do not take account of changes in the importance of variables. We currently work on the incorporation of algorithms that derive additional variables from the longitudinal data and use them in the Discovery module.