Complimentary from the publishers of Predictive Modeling News November 19, 2012 | ||
Fuzzy association rule model used to predict dengue fever outbreaksResearchers developed a method to predict dengue
fever outbreaks utilizing Fuzzy Association Rule Mining to identify
relationships between clinical, meteorological, climatic, and
socio-political data from Peru. The best set of relationships, or rules,
is automatically chosen and forms a classifier, which is then used to
predict future dengue incidence as either HIGH (outbreak) or LOW (no
outbreak). The automated method built three different fuzzy association
rule models. The first two weekly models predicted dengue incidence
three and four weeks in advance, respectively. The third prediction
encompassed a four-week period, four to seven weeks from time of
prediction. The method is general and could be applied in any
geographical region for other environmentally influenced infections. Source: "A data-driven epidemiological prediction
method for dengue outbreaks using local and remote sensing data," BMC
Medical Informatics and Decision Making, November 5, 2012 |
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