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Application of inductive logic programming for learning ECG waveforms

  • Knowledge Acquisition and Learning
  • Conference paper
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Artificial Intelligence in Medicine (AIME 1997)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1211))

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Abstract

In this paper a learning system is presented which integrates an ECG waveform classifier (called PECG) with an interactive learner (called IMPUT). The PECG system is based on an attribute grammar specification of ECGs that has been transformed to Prolog. The IMPUT system combines the interactive debugging technique IDT with the unfolding algorithm introduced in SPECTRE. Using the IMPUT system we can effectively assist in preparing the correct description of the basic structures of ECG waveforms.

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References

  1. Alexin, Z., Gyimóthy, T., Boström, H.: Integrating Algorithmic Debugging and Unfolding Transformation in an Interactive Learner in Proceedings of the 12th European Conference on Artificial Intelligence ECAI-96 ed. Wolfgang Wahlster, Budapest, Hungary (1996) 403–407 John Wiley & Son's Ltd. 1996.

    Google Scholar 

  2. Boström, H., Idestam-Almquist, P.: Specialization of Logic Programs by Pruning SLD-trees., Proc. of the Fourth International Workshop on Inductive Logic Programming (ILP-94) Bad Honnef/Bonn Germany September 12–14. (1994) 31–47

    Google Scholar 

  3. Kókai, G., Alexin, Z., Gyimóthy, T.: Classifying ECG Waveforms in Prolog Proc. of the Fourth International Conference on The Practical Application of PROLOG (PAP96) London, United Kingdom April 23–25, (1996) 193–221

    Google Scholar 

  4. Lavrač, N., Džeroski, S.: Inductive Logic Programming: Techniques and Applications Ellis Horwood, (1994)

    Google Scholar 

  5. Muggleton, S., De Raedt, L.: Inductive Logic Programming: Theory and methods, Journal of Logic Programming 19 (20) (1994) 629–679

    Google Scholar 

  6. Ostrand, T. J., Balker, M. J.: The Category-Partition Method for Specifying and Generating Functional Tests CACM 31:6 June (1988) 676–686

    Google Scholar 

  7. Paakki, J., Gyimóthy, T., Horváth T.,: Effective Algorithmic Debugging for Inductive Logic Programming. Proc. of the Fourth International Workshop on Inductive Logic Programming (ILP-94) Bad Honnef/Bonn Germany September 12–14. (1994) 175–194

    Google Scholar 

  8. Shapiro, E. Y.: Algorithmic Program Debugging MIT Press (1983)

    Google Scholar 

  9. Skordalakis, E.: ECG Analysis in Syntactic and Structural Pattern Recognition Theory and Applications ed. Bunke, H. and Sanfeliu, A. World Scientific (1990) 499–533

    Google Scholar 

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Author information

Authors and Affiliations

  1. Institute of Informatics, József Attila University, Hungary

    Gabriella Kókai

  2. Department of Applied Informatics, József Attila University, Árpád tér 2, H-6720, Szeged, Hungary

    Zoltán Alexin

  3. Research Group on Artificial Intelligence, Hungarian Academy of Sciences, Aradi vértanuk tere 1, H-6720, Szeged, Hungary

    Tibor Gyimóthy

Authors
  1. Gabriella Kókai
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  2. Zoltán Alexin
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  3. Tibor Gyimóthy
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Editor information

Elpida Keravnou Catherine Garbay Robert Baud Jeremy Wyatt

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© 1997 Springer-Verlag Berlin Heidelberg

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Kókai, G., Alexin, Z., Gyimóthy, T. (1997). Application of inductive logic programming for learning ECG waveforms. In: Keravnou, E., Garbay, C., Baud, R., Wyatt, J. (eds) Artificial Intelligence in Medicine. AIME 1997. Lecture Notes in Computer Science, vol 1211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0029443

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  • DOI: https://doi.org/10.1007/BFb0029443

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62709-8

  • Online ISBN: 978-3-540-68448-0

  • eBook Packages: Springer Book Archive

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