| | SLO | ENG | Piškotki in zasebnost

Večja pisava | Manjša pisava

Izpis gradiva

Naslov:Contrasting temporal trend discovery for large healthcare databases
Avtorji:Hrovat, Goran (Avtor)
Štiglic, Gregor (Avtor)
Kokol, Peter (Avtor)
Ojsteršek, Milan (Avtor)
Datoteke:.pdf Contrasting_temporal_trend_discovery_for_large_health_care_database.pdf (1013,97 KB)
 
URL http://www.sciencedirect.com/science/article/pii/S0169260713003040
 
Jezik:Angleški jezik
Vrsta gradiva:Delo ni kategorizirano (r6)
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FERI - Fakulteta za elektrotehniko, računalništvo in informatiko
Opis: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.
Ključne besede:data mining, decision support, trend discovery
Št. strani:str. 251-257
Številčenje:#iss. #1, #Vol. #113
UDK:004.8:61
COBISS_ID:17171222 Povezava se odpre v novem oknu
DOI:10.1016/j.cmpb.2013.09.005 Povezava se odpre v novem oknu
ISSN pri članku:0169-2607
NUK URN:URN:SI:UM:DK:0CATOK93
Število ogledov:881
Število prenosov:198
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
Področja:Ostalo
:
  
Skupna ocena:(0 glasov)
Vaša ocena:Ocenjevanje je dovoljeno samo prijavljenim uporabnikom.
Objavi na:AddThis
AddThis uporablja piškotke, za katere potrebujemo vaše privoljenje.
Uredi privoljenje...

Postavite miškin kazalec na naslov za izpis povzetka. Klik na naslov izpiše podrobnosti ali sproži prenos.

Gradivo je del revije

Naslov:Computer methods and programs in biomedicine
Skrajšan naslov:Comput. methods programs biomed.
Založnik:Elsevier
ISSN:0169-2607
COBISS.SI-ID:25260032 Novo okno

Komentarji

Dodaj komentar

Za komentiranje se morate prijaviti.

Komentarji (0)
0 - 0 / 0
 
Ni komentarjev!

Nazaj
Logotipi partnerjev Univerza v Mariboru Univerza v Ljubljani Univerza na Primorskem Univerza v Novi Gorici