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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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| Publicado no: | BMC Med Inform Decis Mak |
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| Main Authors: | , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2015
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| Assuntos: | |
| Acesso em linha: | 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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