Fuzzy association rule mining and classification for the prediction of malaria in South Korea

BACKGROUND: Malaria is the world’s most prevalent vector-borne disease. Accurate prediction of malaria outbreaks may lead to public health interventions that mitigate disease morbidity and mortality. METHODS: We describe an application of a method for creating prediction models utilizing Fuzzy Assoc...

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Détails bibliographiques
Publié dans:BMC Med Inform Decis Mak
Auteurs principaux: Buczak, Anna L., Baugher, Benjamin, Guven, Erhan, Ramac-Thomas, Liane C., Elbert, Yevgeniy, Babin, Steven M., Lewis, Sheri H.
Format: Artigo
Langue:Inglês
Publié: BioMed Central 2015
Sujets:
Research Article
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC4472166/
https://ncbi.nlm.nih.gov/pubmed/26084541
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12911-015-0170-6
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