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A Hybrid Automatic System for the Diagnosis of Lung Cancer Based on Genetic Algorithm and Fuzzy Extreme Learning Machines

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Abstract

An automatic system for the diagnosis of lung cancer has been proposed in this manuscript. The proposed method is based on combination of genetic algorithm (GA) for the feature selection and newly proposed approach, namely the extreme learning machines (ELM) for the classification of lung cancer data. The dimension of the feature space is reduced by the GA in this scheme and the effective features are selected in this way. The data are then fed to a fuzzy inference system (FIS) which is trained by the fuzzy extreme learning machines approach. The results on real data indicate that the proposed system is very effective in the diagnosis of lung cancer and can be used for clinical applications.

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Authors and Affiliations

  1. Biomedical Engineering Department, Faculty of Electrical Engineering, Iran University of Science and Technology (IUST), Narmak, Tehran, 16846-13114, Iran

    Mohammad Reza Daliri

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  1. Mohammad Reza Daliri
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Correspondence to Mohammad Reza Daliri.

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Daliri, M.R. A Hybrid Automatic System for the Diagnosis of Lung Cancer Based on Genetic Algorithm and Fuzzy Extreme Learning Machines. J Med Syst 36, 1001–1005 (2012). https://doi.org/10.1007/s10916-011-9806-y

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  • DOI: https://doi.org/10.1007/s10916-011-9806-y

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