Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/15962
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dc.contributor.authorJovanović, Marijaen_US
dc.contributor.authorSokić, Dragoslaven_US
dc.contributor.authorGrabnar, Iztoken_US
dc.contributor.authorVovk, Tomažen_US
dc.contributor.authorProstran, Milicaen_US
dc.contributor.authorErić, Slavicaen_US
dc.contributor.authorKuzmanovski, Igoren_US
dc.contributor.authorVučićević, Katarinaen_US
dc.contributor.authorMiljković, Branislavaen_US
dc.date.accessioned2021-12-30T08:33:02Z-
dc.date.available2021-12-30T08:33:02Z-
dc.date.issued2015-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/15962-
dc.description.abstractThe application of artificial neural networks in the pharmaceutical sciences is broad, ranging from drug discovery to clinical pharmacy. In this study, we explored the applicability of counter-propagation artificial neural networks (CPANNs), combined with genetic algorithm (GA) for prediction of topiramate (TPM) serum levels based on identified factors important for its prediction.en_US
dc.language.isoenen_US
dc.relation.ispartofJournal of pharmacy & pharmaceutical sciences : a publication of the Canadian Society for Pharmaceutical Sciences, Societe canadienne des sciences pharmaceutiquesen_US
dc.titleApplication of Counter-propagation Artificial Neural Networks in Prediction of Topiramate Concentration in Patients with Epilepsyen_US
dc.identifier.doi10.18433/j33031-
dc.identifier.volume18-
dc.identifier.issue5-
item.grantfulltextnone-
item.fulltextNo Fulltext-
crisitem.author.deptFaculty of Natural Sciences and Mathematics-
Appears in Collections:Faculty of Natural Sciences and Mathematics: Journal Articles
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