Fuzzy Knowledge Discovery and Decision-Making Through Clustering and Dynamic Tables: Application in Medicine
The objective of this study was to design, to implement and to validate a framework for the development of decision system support based on fuzzy set theory using clusters and dynamic tables. To validate the proposed framework, a fuzzy inference system was developed with the aim to classify breast cancer and compared with other related works (Literature). The fuzzy Inference System has three input variables. The results show that the Kappa Statistics and accuracy were 0.9683 and 98.6%, respectively for the output variable for the Fuzzy Inference System – FIS, showing a better accuracy than some literature results. The proposed framework may provide an effective means to draw a pattern to the development of fuzzy systems.
KeywordsClustering Dynamic tables Fuzzy sets Breast cancer
The first author expresses his deep thanks to the Administrative Department of Science, Technology, and Innovation – COLCIENCIAS of Colombia and the Universidad del Norte for the Doctoral scholarship. Also expresses their deep thanks to the Universidad del Sinú Elías Bechara Zainúm for the scholar and financial support.
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