Abstract
Headache, medically known as cephalalgia, may have a wide range of symptoms and its types may be related and mixed. Its proper diagnosis is difficult and automatic diagnosis is usually rather imprecise, therefore, the problem is still the focus of intensive research. In the paper we propose headache diagnosis method which makes the decision on the basis of questionnaire only. It distinguished among 11 headache classes, which taxonomy is provided. The paper presents results of experiments which aim at selecting the best classification algorithm including several classical machine learning methods as well as ensemble approach. Results of experiments carried on dataset collected in University of Novi Sad confirm that the automatic classification system can gain high accuracy of classification for the problem under consideration.
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Jackowski, K., Jankowski, D., Ksieniewicz, P., Simić, D., Simić, S., Woźniak, M. (2014). Ensemble Classifier Systems for Headache Diagnosis. In: Piętka, E., Kawa, J., Wieclawek, W. (eds) Information Technologies in Biomedicine, Volume 4. Advances in Intelligent Systems and Computing, vol 284. Springer, Cham. https://doi.org/10.1007/978-3-319-06596-0_25
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DOI: https://doi.org/10.1007/978-3-319-06596-0_25
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-06595-3
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