Abstract

RIVERO CASTRO, Arelys; CRUZ CORREA, Luis Manuel  and  ARTILES LEZCANO, Jeffrey. Algorithm selection for classifying Solitary Pulmonary Nodules. RCIM [online]. 2016, vol.8, n.2, pp. 166-177. ISSN 1684-1859.

In recent years the international scientific community has devoted considerable resources to research and development of systems for computer-aided diagnosis used by physicians in the diagnostic process. Special attention has been provided in some medical areas, such as oncology specialties, by high mortality rates caused by some diseases like lung cancer. Early diagnosis of this condition can greatly reduce these indicators and improve quality of life of patients.The objective pursued with the development of this research is the proper selection of a classification algorithm, to be used in the phase that has the same name, as part of a system of computer-aided diagnosis for classification of solitary pulmonary nodules. For the selection of the appropriate classification algorithm, an experiment was performed using the tools Weka v3.7.10 and Matlab 2013. To determine which of the techniques studied produces better performance results, the same data set was used for the phases of training, testing and validation of the classifier, available in the international database The Lung Image Database Consortium Image Collection.

Keywords : classification algorithm; machine learning; solitary pulmonary nodules; accuracy.

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