Bayesian classification (AutoClass): theory and results
Advances in knowledge discovery and data mining
Bayesian biosurveillance of disease outbreaks
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Learning Bayesian Networks
A Bayesian network for outbreak detection and prediction
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Why is diagnosis using belief networks insensitive to imprecision in probabilities?
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Journal of Biomedical Informatics
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An epidemic curve is a graph in which the number of new cases of an outbreak disease is plotted against time. Epidemic curves are ordinarily constructed after the disease outbreak is over. However, a good estimate of the epidemic curve early in an outbreak would be invaluable to health care officials. Currently, techniques for predicting the severity of an outbreak are very limited. As far as predicting the number of future cases, ordinarily epidemiologists simply make an educated guess as to how many people might become affected. We develop a model for estimating an epidemic curve early in an outbreak, and we show results of experiments testing its accuracy.