The Community for Technology Leaders
2011 IEEE International Conference on Bioinformatics and Biomedicine (2011)
Atlanta, Georgia USA
Nov. 12, 2011 to Nov. 15, 2011
ISBN: 978-0-7695-4574-5
pp: 321-326
ABSTRACT
In this paper, a new approach based on Differential Evolution for the automatic classification of items in medical databases is proposed. Based on it, a tool called DERExis presented, which automatically extracts explicit knowledge from the database under the form of IF -- THEN rules. DERExis thought as a useful support to decision making whenever explanations on why an item is assigned to a given class should be provided, as it is the case for diagnosis in the medical domain. The tool has been compared over seven medical databases against a set of fifteen classification tools widely used in literature. The results have proven the effectiveness of the proposed approach, since DEREx turns out to be among the very best tools in terms of highest classification accuracy, so it is preferable because it automatically extracts knowledge and provides users with it under an easily comprehensible form.
INDEX TERMS
Decision Support System, Medical Diagnosis, Classification, Automatic Rule Extraction, Differential Evolution
CITATION

I. De Falco, "A Differential Evolution-Based System Supporting Medical Diagnosis through Automatic Knowledge Extraction from Databases," 2011 IEEE International Conference on Bioinformatics and Biomedicine(BIBM), Atlanta, Georgia USA, 2011, pp. 321-326.
doi:10.1109/BIBM.2011.63
379 ms
(Ver 3.3 (11022016))