Case-based reasoning as a decision support system for cancer diagnosis: A case study

Issue title: Data Mining and Hybrid Intelligent Systems

Guest editors: Fatos Xhafa, Francisco Herrera and Mario Köppen

Article type: Research Article

Authors: De Paz, Juan F. | Rodríguez, Sara | Bajo, Javier^{; *} | Corchado, Juan M.

Affiliations: Departamento de Informática y Automática, Universidad de Salamanca, Plaza de la Merced s/n, 37008, Salamanca, España. E-mails: [email protected], [email protected], [email protected], [email protected]

Correspondence: [*] Corresponding author: Javier Bajo, Compañía 5, 37002, Salamanca, Spain. Tel.: +34 639771985; Fax: +34 923277101; E-mail: [email protected]

Abstract: Microarray technology can measure the expression levels of thousands of genes in an experiment. This fact makes the use of computational methods in cancer research absolutely essential. One of the possible applications is in the use of Artificial Intelligence techniques. Several of these techniques have been used to analyze expression arrays, but there is a growing need for new and effective solutions. This paper presents a Case-based reasoning (CBR) system for automatic classification of leukemia patients from microarray data. The system incorporates novel algorithms for data mining that allow filtering, classification, and knowledge extraction. The system has been tested and the results obtained are presented in this paper.

Keywords: Case-based reasoning, HG U133, ESOINN, leukemia classification, decision tree

DOI: 10.3233/HIS-2009-0089

Journal: International Journal of Hybrid Intelligent Systems, vol. 6, no. 2, pp. 97-110, 2009