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A Neural Net Learning Algorithm for Design of Cardiotocograph Signal Evaluation Expert System: MYDEARBABY 90/2.47

  • M. Umit Karakas
  • Yoh-Han Pao
  • M. Sinan Beksac
  • Kadir Ozdemir

Abstract

An Expert System (MYDEARBABY) for Evaluating Fetal Heart Rate (FHR) variations of an unborn baby has been developed using an ad-hoc Production Rule Technique (version 2.34) and Neural Network Technique (version 2.47). The training set contains 219 recordings from mostly at-risk patients. In Neural Netvork version of the expert system single layer Neural Net (functional link net) with 17 inputs, 1 output parameter are used.

Keywords

Expert System Medical Doctor Production Rule Fetal Heart Rate Fractional Power 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Rosenblatt, F., 1961. Principles of neurodynamics, perceptrons and the theory of brain mechanism, Spartan, Washington, D.C.Google Scholar
  2. 2.
    Nilsson, N.J., 1965. Learning machines, McGraw-Hill, New York, NY.MATHGoogle Scholar
  3. 3.
    Minsky R. and S. Papert, 1969. Perceptron: An introduction to computational geometry, MIT Press, Cambridge.Google Scholar
  4. 4.
    Newell, A., 1983. Intellectual issues in the history of artificial intelligence, F. Machlap and U. Mansfield (Eds.), John Wiley and Sons, New York, NY.Google Scholar
  5. 5.
    Kohonen, T., 1982. Self organized formation of topologically correct maps, Biological Cybernetics, Vol. 43, pp. 59–69.MathSciNetMATHCrossRefGoogle Scholar
  6. 6.
    Kohonen, T., 1982. Clustering, taxonomy and topological maps of patterns, CH, IEEE, pp. 114–128.Google Scholar
  7. 7.
    Rumelhart, D.E., G.E. Hinton, and R J. Williams, 1986. Learning internal representations by error propagation, in Parallel Distributed Processing: Explorations in the Microstructures of Cognition: Foundations, Vol. 1, pp. 318–362, D.E. Rumelhart and J.L. McClelland (Eds.), MIT Press, Cambridge, MA.Google Scholar
  8. 8.
    Pao, Y.H., 1989. Adaptive pattern recognition and neural networks, Addison-Wesley, Reading, MA.MATHGoogle Scholar
  9. 9.
    Hinton, G.E., 1989. Connectionist learning procedures, Artificial Intelligence 40, pp. 185–234.CrossRefGoogle Scholar
  10. 10.
    Tesauro, G. and T.J. Segnowski, 1989. A parallel network that learns to play backgammon, Artificial Intelligence, Vol. 30, No. 3, pp. 357–390.CrossRefGoogle Scholar
  11. 11.
    Gorman, R.P. and T.J. Segnowski, 1988. Analysis of hidden units in a layered network trained to classify sonar targets, Neural Networks 1, pp. 75–89.CrossRefGoogle Scholar
  12. 12.
    Prager, R.W., T.D. Harrison, and F. Fallside, 1987. Boltzmann machines for speech recognition, Compt. Speech Lang. 1, pp. 3–27.CrossRefGoogle Scholar
  13. 13.
    Pao, Y.H., D.J. Sobajic, and J.J. Lu, 1988. Neural-net implementations of pattern-based controls for robotic motion, Proceedings of the IMACS World Congress, Paris, France, July 18–22.Google Scholar
  14. 14.
    Sobajic, D.J., J.J. Lu, and Y.H. Pao, 1988. Intelligent control of the intelledex 605T robot manipulator, International Workshop NEURONIMES 88, Nimes, France, November 15–18.Google Scholar
  15. 15.
    Sobajic, D.J. and Y.H. Pao, 1988. Artificial neural-net based dynamic security assessment for electric power systems, IEEE/Power Engineering Society 1988 Winter Meeting, February 5, 1988, paper 88WM211–5, also published in the IEEE Transactions on Power Systems, Vol. 4, pp. 220–228, 1989.CrossRefGoogle Scholar
  16. 16.
    Karakas, U., S. Beksac, S. Ergincan, F. Girgin, H. Koymen, and F. Tuzun, 1988. An obstretric database and cardiotocograph interface: MYDEARBABY v. 1.0, Seventh National Informatique Conference Turkey, September 22–24, 1988, Eskisehir, Turkey, pp. 23–334, in Turkish.Google Scholar
  17. 17.
    Karakas, U., S. Beksac, S. Ergincan, F. Girgin, H. Koymen, and F. Tuzun, 1988. Expert system for evaluating fetal monitor signals: MYDEARBABY v. 2.13, Third International Symposium on Computer and Information Sciences, October 29-November 2, 1988, Cesme, Izmir, Turkey, pp. 381–386, invited presentation.Google Scholar
  18. 18.
    . Beksac, S, U. Karakas,,S. Yalcin, K. Ozdemir, and E. Sanliturk, 1989. Computerized analysis of antepartum fetal heart rate tracings in normal pregnancies: version 88/2.29, presented by Beksac-Karakas at Vila Real, Portugal, Septemember 28 - October 1, 1989, EEC Concerted Action Project Workshop on Validity of Cardiotocography, will appear on European Journal of Obst. & Gyn. Google Scholar
  19. 19.
    Beksac, S., K. Ozdemir, U. Karakas, S. Yalcin, and E. Karaagaoglu. Development and application of a simple expert system for the interpretation of the antepartum fetal heart rate tracings, version 88/2.29, will appear on European Journal of Obst. & Gyn. Google Scholar
  20. 20.
    Cohen, M.E., D.L. Hudson, and M.F. Anderson, 1989. A neural network learning algorithm with medical applications, The 13th Annual Symposium on Computer Applications in Medical Care (SCAMC-89), November 5–8, 1989, Washington, D.C., IEEE Computer Society Press, 1989, pp. 307–311.Google Scholar
  21. 21.
    Meistrell, K.A. and K.A. Spackman. Evaluation of neural network performance by receiver operating characteristic analysis: Examples from the biotechnology domain, SCAMC-89, pp. 235–301.Google Scholar
  22. 22.
    Coffey, D. and G. Banks, 1989. A connectionist visual field analyzer, SCAMC-89, pp. 276–282.Google Scholar
  23. 23.
    Smith, J.H., K.S.J. Anand, P.M. Cotes, G.S. Dawes, R.A. Harkness, T.A. Howlett, and C.W.G. Redman, 1988. Ante-natal fetal heart rate variations in relation to the respiratory and metabolic status of the compromised human fetus, British Journal of Obst. & Gyn. Google Scholar
  24. 24.
    Searle, J.R., L.D. Devoe, M.C. Phillips, and N.S. Searle, 1988. Computerized analysis of resting fetal heart rate tracings, American Jour. of Obst. & Gyn., March, 1988, No. 71, pp. 401–411.Google Scholar
  25. 25.
    Caron, F.J., H.P. van Geijin, E.E. van Woerden, J.M. Swartjes, and R. Mantel, 1988. Computerized assessment of fetal behavioral states, Journal of Prenatal Medicine (Berlin),No. 16, Vol. 4, pp. 365–372.Google Scholar
  26. 26.
    Mendez-Bauer, C., S. Schuman, B. Tran, A. Chun, M. Cheung, S. Porges, and U. Freese, 1987. Computer assisted interpretation of fetal monitor tracings, First World Symp. on Computers in the Care of Mother Fetus and Newborn, Wien, Austria, March 8–12, 1987.Google Scholar
  27. 27.
    Jongsmdt, H.W., D.K. Donker, J.S. Duisterhout, and H.P. vanGeijn, 1987. A data base of visually described cardiotocograms, Journ. of Perinotal Medicine (Berlin), No. 15, Suppl. 1.Google Scholar
  28. 28.
    Pao, Y.H., 1989. Functional link nets: Removing hidden layers, AI Expert, Vol. 4, pp. 60–68.Google Scholar
  29. 29.
    Pao, Y.H., 1989. N-NET Neural net development system user manual, AI WARE, Inc., 11000 Cedar Avenue, Cleveland, OH, 44106.Google Scholar

Copyright information

© Springer-Verlag/Wien 1990

Authors and Affiliations

  • M. Umit Karakas
    • 1
    • 2
  • Yoh-Han Pao
    • 2
  • M. Sinan Beksac
    • 1
  • Kadir Ozdemir
    • 1
  1. 1.Hacettepe UniversityAnkaraTurkey
  2. 2.Case Western Reserve UniversityClevelandUSA

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