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The Challenge of Soft Computing Techniques for Tumor Characterization

  • Conference paper
Artificial Intelligence and Soft Computing - ICAISC 2004 (ICAISC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3070))

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Abstract

Computational diagnosis tools are becoming indispensable to support modern medical diagnosis. This research work introduces an hybrid soft computing scheme consisting of Fuzzy Cognitive Maps and the effective Active Hebbian Learning (AHL) algorithm for tumor characterization. The proposed method exploits human experts’ knowledge on histopathology expressed in descriptive terms and concepts and it is enhanced with Hebbian learning and then it classifies tumors based on the morphology of tissues. This method was validated in clinical data and the results enforce the effectiveness of the proposed approach.

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Patras, GR–26500, Patras, Greece

    E. I. Papageorgiou & P. P. Groumpos

  2. Computer Laboratory, School of Medicine, University of Patras, GR 26500, Patras, Greece

    P. P. Spyridonos & G. C. Nikiforidis

  3. Department of Computer Science, University of Ioannina, GR 1186, Ioannina, Greece

    C. D. Stylios

  4. Department of Pathology, University Hospital of Patras, GR 26500, Patras, Greece

    P. Ravazoula

Authors
  1. E. I. Papageorgiou
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  2. P. P. Spyridonos
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  3. C. D. Stylios
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  4. P. Ravazoula
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  5. G. C. Nikiforidis
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  6. P. P. Groumpos
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. German Research Center of Artificial Intelligence (DFKI), Germany

    Jörg H. Siekmann

  3. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Initiative in Soft Computing (BISC), 94720-1776, Berkeley, CA

    Lotfi A. Zadeh

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© 2004 Springer-Verlag Berlin Heidelberg

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Papageorgiou, E.I., Spyridonos, P.P., Stylios, C.D., Ravazoula, P., Nikiforidis, G.C., Groumpos, P.P. (2004). The Challenge of Soft Computing Techniques for Tumor Characterization. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_161

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  • DOI: https://doi.org/10.1007/978-3-540-24844-6_161

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22123-4

  • Online ISBN: 978-3-540-24844-6

  • eBook Packages: Springer Book Archive

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