Abstract
Architecture and learning method for evolving diagnostic neuro-fuzzy-system for Medical Data Mining tasks in situation of uncertainty about quantities of attributes and diagnoses are proposed. Diagnostic neuro-fuzzy-system was approbated on data set, which present erosive ulcerous disease of the gastrointestinal tract and shown high quality of classification in condition of different quantity of input and output data.
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References
Jang, J.-S.R., in Neuro-fuzzy and Soft Computing, Jang, J.-S.R., Sun, C.-T., and Mizutani, E., Eds., Prentice Hall, Upper Saddle River, NJ, 1997.
Friedman, J., in The Elements of Statistical Learning. Data Mining, Inference and Prediction, Friedman, J., Hastie, T., and Tibshirani, R., Eds., Berlin: Springer, 2003.
Osowski, S., Sieci neuronowe do przetwarzania informacji, Warszawa: Oficina Wydawnicza Politechniki Warszawskiej, 2006.
Ruthowski, L., Computational Intelligence. Methods and Techniques, Berlin-Heidelberg, 2008.
Mumford, C.L. and Jain, L.C., Computational intelligence. Collaboration, fusion and Emergence, Berlin: Springer-Verlag, 2009.
Kruse, R., Borgelt, C., Klawonn, F., Moewes, C., Steinbrecher, M., and Held, P., Computational Intelligence. Methodological Introduction, Berlin: Springer-Verlag, 2013.
Kroll, A., Computational Intelligence. Eine Einführung in Probleme, Methoden und technische Anwendungen, Munchen: Oldenbourg Verlag, 2013.
Du, K.-L. and Swami, M.N.S., Neural Networks and Statistical Learning, London: Springer-Verlag, 2014.
Nauck, D. and Kruse, R., NEFCLASS—a neuro-fuzzy approach for the classification of data, Proc. of the 1995 ACM Symposium on Applied Computing, “Applied Computing 1995,” George, K.M., Ed., Nashville, 1995, 461–465.
Bifet, A., Adaptive Stream Mining. Pattern Learning and Mining from Evolving Data Streams, Amsterdam: IOS Press, 2010.
Rizzo, R., Computational intelligence methods for bioinformatics and biostatistics, 7th International Meeting, CIBIB 2010, Palermo, Italy, September 16–18, 2010, Rizzo, R., Eds., Springer, 2011.
Kountchev, R., Advances in Intelligent Analysis of Medical Data and Decision Support Systems (Studies in Computational Intelligence), Kountchev, R., et al., Eds., Springer-Verlag, Berlin Heidelberg, 2013.
Bodyanskiy, Ye.V., Vynokurova, O., Mulesa, P.P., and Perova, I.G., Diagnostic neuro-fuzzy system and its adaptive learning algorithm in the medical and biological data mining tasks, Syst. Technol., 2014, no. 2 (91).
Wang, L.X. and Mendel, J.M., Fuzzy basis functions, universal approximation, and orthogonal least squares learning, IEEE Trans. Neural Network, 1992, no. 3, pp. 807–814.
Shynk, J.J., Performance surfaces of a single-layer perceptron, IEEE Trans. Neural Networks, 1990, no. 1, pp. 268–274.
Shepherd, A.J., Second-Order Methods for Neural Networks, London: Springer-Verlag, 1997.
Otto, P., Bodyanskiy, Ye., and Kolodyazhniy, V., A new learning algorithm for forecasting neural-fuzzy network, Integr. Comput.-Aided Eng., 2003, vol. 10, no. 4, pp. 399–409.
Kasabov, N., Evolving Connectionist Systems: Methods and Applications in Bioinformatics, Brain Study and Intelligent Machines, London: Springer-Verlag, 2003.
Lughofer, E., Evolving Fuzzy Systems—Methodologies, Advanced Concept and Applications, Berlin-Heidelberg: Springer-Verlag, 2011.
Perova, I. and Bodyanskiy, Ye., Fast evolving diagnostic neuro-fuzzy system and its learning in medical data mining tasks, Syst. Technol., 2015, no. 6 (101), pp. 109–116.
Gelfand, B.R., Sepsis in the beginning of XXI century, in Guidelines, Moscow, 2004.
Rauws, E.A.J., Langenberg, W., Houthoff, H.J., Zanen, H.C., and Tytgat, G.N.J., Campylobacter pyloridisassociated chronic antral gastritis. A prospective study of its prevalence and the effects of antibacterial and antiulcer treatment, Gastroenterol., 2005, vol. 94, pp. 33–40.
Bodyanskiy, Ye., Pavlov, O., and Vynokurova, O., in Outliers Resistant Learning Algorithm for Radial-basisfuzzy-wavelet-neural Network in Stomach Acute Injury Diagnosis Tasks, Markov, K., Ivanova, K., and Mitov, I., Eds., Sofia: Institute of Information Theories and Application FOI ITHEA, 2008.
Boyko, V.V., Sushkov, S.V., Pavlov, O.O., and Vynokurova, O.A., The Anesthesia and Intensive Therapy Strategy in the Acute Gastro Ileum Hemorrhage, Kharkiv: Eksklusiv, 2007.
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Pliss, I., Perova, I. Diagnostic Neuro-Fuzzy System and Its Learning in Medical Data Mining Tasks in Conditions of Uncertainty about Numbers of Attributes and Diagnoses. Aut. Control Comp. Sci. 51, 391–398 (2017). https://doi.org/10.3103/S0146411617060062
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DOI: https://doi.org/10.3103/S0146411617060062