A fuzzy decision tree based approach to characterize medical data

In this paper, two medical experiments are presented where the use of a fuzzy machine learning tool brought out a better understanding of the patients involved in the study. The use of fuzzy set theory to provide fuzzy labels and the construction of fuzzy decision trees to generate fuzzy rule bases enhance greatly the understandability and enable the medical scientists to have a better understanding of the correlations between the description of the patients and their medical class. The results obtained in these two experiments highlight the usefulness of fuzzy data mining approach to handle real world data and to benefit society.