20.500.12556/DKUM-10183 PODATKOVNO RUDARJENJE V LEKARNIŠKI DEJAVNOSTI DATA MINING IN FARMACY V diplomski nalogi so najprej opisane osnovne metode in algoritmi podatkovnega rudarjenja, kot so linearna regresija, histogram, analiza gruc, povezovalna pravila odlocitvena drevesa, nevronske mreže, algoritem K–ti najbližji sosed in algoritem C4.5. Na podrocju oskrbe bolnikov z zdravili so se pokazale potrebe po rudarjenju po podatkovnih bazah tudi v farmacevtski dejavnosti. Z uporabo algoritma C4.5 za gradnjo odlocitvenih dreves v orodju WEKA smo iz podatkov lekarniške podatkovne baze ugotavljali zakonitosti pri predpisovanju registriranih zdravil. The first part of diploma paper deals with data mining basic methods and algorithms, such as linear regression, histogram, cluster analysis, binding rules, decision trees, neural networks, K-nearest neighbour, and the C4.5 algorithm. In the field of treating patients with drugs, a need for data mining arose in pharmaceutical business as well. Using C4.5 algorithm for building decision trees in WEKA tool and information from the pharmacy database we were assessing basic rules that apply in prescribing registered drugs. podatkovno rudarjenje polifarmakoterapija polipragmazija interakcije med zdravili WEKA. data mining polypharmacy polypragmasy drug interaction WEKA. true true false [V. Pečnik] Slovenski jezik Angleški jezik Diplomsko delo 2009-04-20 19:20:48 2012-02-02 10:02:57 2022-04-11 16:03:56 2022-04-16 03:14:46 2009 0 Maribor 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.6 51131907 URN:SI:UM:DK:KWK4OB9S VS_Pecnik_Vlado_2009.pdf VS_Pecnik_Vlado_2009.pdf 1 3692FABC0E6A6F72C665EE5DA23A44DB 498a584d780fafd8814c6ac45dedb258acac3b3040095b46acd1940b22a5e375 bf71ff22-7c02-11eb-bb7a-00155d0001ca 20.500.12556/dkum/8f7917b0-084f-41d7-813e-9a43643ddc51 https://dk.um.si/Dokument.php?lang=slv&id=8190 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0