Abstract
Influenza is the last of the classic plagues of the past, which still has to be brought under control. It causes a lot of costs: prolonged stays in hospitals and especially many days of unfitness for work. Therefore many of the most developed countries have started to create influenza surveillance systems. Mostly statistical methods are applied to predict influenza epidemics. However, the results are rather moderate, because influenza waves occur in irregular cycles. We have developed a method that combines Case-Based Reasoning with temporal abstraction. Here we compare experimental results of our method and of statistical methods.
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Schmidt, R., Waligora, T. (2007). Influenza Forecast: Case-Based Reasoning or Statistics?. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74819-9_36
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DOI: https://doi.org/10.1007/978-3-540-74819-9_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74817-5
Online ISBN: 978-3-540-74819-9
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