Machine learning applied to diagnosis of sport injuries
- 169 Downloads
Several machine learning algorithms were used in the development of an expert system for diagnosing sport injuries. The applied methods include variants of the Assistant algorithm for top-down induction of decision trees, and variants of the Bayesian classifier. Since the available dataset turned out to be insufficent for reliable diagnosis of selected sport injuries, expert-defined diagnostic rules were added and used in combination with classifiers induced by machine learning systems. Experimental results show that the classification accuracy and the explanation capability of the naive Bayesian classifier with the fuzzy discretization of numerical attributes was superior to other methods and therefore the most appropriate for practical use in our application.
Unable to display preview. Download preview PDF.
- 1.Cestnik, B., Kononenko, I., and Bratko, I. (1987). ASSISTANT 86: A knowledge elicitation tool for sophisticated users. In I. Bratko and N. Lavrač, editors, Progress in Machine Learning, pages 31–45. Sigma Press, Wilmslow.Google Scholar
- 2.Kononenko, I. (1993). Inductive and Bayesian learning in medical diagnosis. Applied Artificial Intelligence, 7:317–337.Google Scholar
- 3.Kononenko, I. and Šimec, E. (1995). Induction of decision trees using RELIEFF. In: G. Della Riccia, R. Kruse and R. Viertl (eds.), Proc. of ISSEK Workshop on Mathematical and statistical methods in Artificial Intelligence, (Udine, September 1994), Springer Verlag, pp.199–220.Google Scholar