20.500.12556/DKUM-46894 Contrasting temporal trend discovery for large healthcare databases With the increased acceptance of electronic health records, we can observe theincreasing interest in the application of data mining approaches within this field. This study introduces a novel approach for exploring and comparingtemporal trends within different in-patient subgroups, which is basedon associated rule mining using Apriori algorithm and linear model-based recursive partitioning. The Nationwide Inpatient Sample (NIS), Healthcare Costand Utilization Project (HCUP), Agency for Healthcare Research and Qualitywas used to evaluate the proposed approach. This study presents a novelapproach where visual analytics on big data is used for trend discovery in form of a regression tree with scatter plots in the leaves of the tree. Thetrend lines are used for directly comparing linear trends within a specified time frame. Our results demonstrate the existence of opposite trendsin relation to age and sex based subgroups that would be impossible to discover using traditional trend-tracking techniques. Such an approach can be employed regarding decision support applications for policy makers when organizing campaigns or by hospital management for observing trends that cannot be directly discovered using traditional analytical techniques. data mining decision support trend discovery true true false Angleški jezik Angleški jezik Delo ni kategorizirano 2014-11-25 15:03:42 2014-11-27 16:27:47 2022-05-19 03:06:33 2021-05-04 03:23:59 0 0 0 str. 251-257 #iss. #1 #Vol. #113 Jan. 2014 0000-00-00 Zaloznikova NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.8:61 25260032 17171222 10.1016/j.cmpb.2013.09.005 0169-2607 URN:SI:UM:DK:0CATOK93 Contrasting_temporal_trend_discovery_for_large_health_care_database.pdf Contrasting_temporal_trend_discovery_for_large_health_care_database.pdf 1 F8E3358D445F7DB02277320CB0426A1F 31f80b4da927c4f1f017c8ca93d7c2f44b2b0b44bee58dc3524c2133394baa3e 70ec025f-7c0b-11eb-bb7a-00155d0001ca https://dk.um.si/Dokument.php?lang=slv&id=68971 http://www.sciencedirect.com/science/article/pii/S0169260713003040 1 https://dk.um.si/Dokument.php?lang=slv&id=68970 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0