Abstract
The main goal of our research was attempt to answer the question, if machine learning algorithms could be applied in computer aided medical diagnostics. Executed tests proven, that data mining methods based on machine learning can be used in medical diagnostics, but it can not substitute an expert, especially in case of rare diseases.
Classifiers induced from revised datasets have better classification accuracy. It is indicating that quality of training data has significant influence for induced classifier accuracy.
In expert opinion of expert, the most of obtained decision rules are consistent with medical knowledge. All cases of incorrect classification were caused by insufficient mathematical model. The evaluation of exact mathematical model in medicine is very difficult.
In this paper results of experiments on two popular machine learning algorithms were presented. The appliance of other classification methods, like Bayesian classifiers, neural networks and fuzzy sets, is subject of future research.
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Penar, W., Wozniak, M. (2005). Machine Learning Methods for Dialysis Therapy Decision Problem — Comparative Study. In: Kurzyński, M., Puchała, E., Woźniak, M., żołnierek, A. (eds) Computer Recognition Systems. Advances in Soft Computing, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32390-2_77
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DOI: https://doi.org/10.1007/3-540-32390-2_77
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25054-8
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