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Combining Fuzzy Cognitive Maps with Support Vector Machines for Bladder Tumor Grading

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4251))

Abstract

Fuzzy Cognitive Map (FCM) is an advanced modeling methodology that provides flexibility on the system’s design, modeling, simulation and control. This research work combines the Fuzzy Cognitive Map model for tumor grading with Support Vector Machines (SVMs) to achieve better tumor malignancy classification. The classification is based on the histopathological characteristics, which are the concepts of the Fuzzy Cognitive Map model that was trained using an unsupervised learning algorithm, the Nonlinear Hebbian Algorithm. The classification accuracy of the proposed approach is 89.13% for High Grade tumor cases and 85.54%, for tumors of Low Grade. The results of the proposed hybrid approach were also compared with other conventional classifiers and are very promising.

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Author information

Authors and Affiliations

  1. Laboratory for Automation and Robotics, Department of Electrical and Computer Engineering, University of Patras, Rion, 26500, Greece

    Elpiniki Papageorgiou, George Georgoulas & Peter Groumpos

  2. Department of Communications, Informatics and Management, TEI of Epirus, 47100, Artas, Greece

    Chrysostomos Stylios

  3. Computer Laboratory, School of Medicine, University of Patras, Rion, 26500, Greece

    George Nikiforidis

Authors
  1. Elpiniki Papageorgiou
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  2. George Georgoulas
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  3. Chrysostomos Stylios
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  4. George Nikiforidis
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  5. Peter Groumpos
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Editor information

Editors and Affiliations

  1. School of Design, Engineering and Computing, Bournemouth University, UK

    Bogdan Gabrys

  2. Centre for SMART Systems, School of Environment and Technology, University of Brighton, BN2 4GJ, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, Mawson Lakes, 5095, SA, Australia

    Lakhmi C. Jain

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© 2006 Springer-Verlag Berlin Heidelberg

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Papageorgiou, E., Georgoulas, G., Stylios, C., Nikiforidis, G., Groumpos, P. (2006). Combining Fuzzy Cognitive Maps with Support Vector Machines for Bladder Tumor Grading. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11892960_63

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  • DOI: https://doi.org/10.1007/11892960_63

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46535-5

  • Online ISBN: 978-3-540-46536-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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