Abstract
This paper presents an overview of the Supervised Classification Techniques that can be applied in medicine. Supervised Classification concerns to the Machine Learning area, and many paradigms have been used in order to develop Decision Support Systems that could help the physician in the diagnosis task. Different families of classifiers can be distinguished based on the model used to do the final classification: Classification Rules, Decision Trees, Instance Based Learning and Bayesian Classifiers are presented in this paper. These techniques have been extended to many research and application fields, and some examples in the medical world are presented for each paradigm.
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© 2001 Springer-Verlag Berlin Heidelberg
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Sierra, B., Inza, I., Larrañaga, P. (2001). On Applying Supervised Classification Techniques in Medicine. In: Crespo, J., Maojo, V., Martin, F. (eds) Medical Data Analysis. ISMDA 2001. Lecture Notes in Computer Science, vol 2199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45497-7_2
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DOI: https://doi.org/10.1007/3-540-45497-7_2
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