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Exploratory Data Mining for Subgroup Cohort Discoveries and Prioritization
2019
IEEE journal of biomedical and health informatics
Finding small homogeneous subgroup cohorts in large heterogeneous populations is a critical process for hypothesis development in biomedical research. Concurrent computational approaches are still lacking in robust answers to the question "what hypotheses are likely to be novel and to produce clinically relevant results with well thought-out study designs?" We have developed a novel subgroup discovery method which employs a deep exploratory mining process to slice and dice thousands of
doi:10.1109/jbhi.2019.2939149
pmid:31494566
pmcid:PMC9341221
fatcat:n7evwo55u5ebjintvtojfr57yu