Abstract
This paper presents a method for the identification of the dynamics of non-linear patho-physiological systems by learning from data. The key idea which underlies our approach consists in the integration of qualitative modeling methods with fuzzy logic systems. The major advantage which derives from such an integrated framework lies in its capability both to represent the structural knowledge of the system at study and to exploit the available experimental data, so that a functional approximation of the system dynamics can be determined and used as a reasonable predictor of the patient's future state. As testing ground of our method, we have considered the problem of identifying the response to the insulin therapy from insulin-dependent diabetic patients: the results obtained are presented and discussed in the paper.
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References
M. Berger and D. Rodbard. Computer simulation of Plasma insulin and glucose dynamics after subcutaneous insulin injection, Diabetes Care, 12 (1989) 725–736.
E.R. Carson, C. Cobelli, and L. Finkenstein. The Mathematical Modeling of Metabolic and Endocrine Systems. Wiley, New York, 1983.
L. Ironi, M. Stefanelli, and G. Lanzola. Qualitative models in medical diagnosis. Artificial Intelligence in Medicine, 2:85–101, 1990.
J. Jang. Anfis: Adaptive network based fuzzy inference system. IEEE Trans. on Systems, Man and Cybernetics, 23:665–685, 1993.
T. Khannah. Foundations of neural networks. Addison-Wesley, Reading, MA, 1990.
B. J. Kuipers. Qualitative Reasoning: modeling and simulation with incomplete knowledge. MIT Press, Cambridge MA, 1994.
H.M. Kim, J.M. Mendel. Fuzzy Basis Functions: Comparison with Other Basis Functions, IEEE Trans. Fuzzy Systems, 3 (1995) 158–168.
E.D. Lehmann and T. Deutsch. A physological model of glucose-insulin interaction in type 1 diabetes mellitus. Biomedical Engineering, 14:235–242, 1992.
L.X. Wang. Adaptive Fuzzy Systems and Control, Prentice hall, Engelwood Cliffs, N.J., 1994.
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© 1997 Springer-Verlag Berlin Heidelberg
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Bellazzi, R., Ironi, L., Guglielmann, R., Stefanelli, M. (1997). Learning from data through the integration of qualitative models and fuzzy systems. 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/BFb0029484
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DOI: https://doi.org/10.1007/BFb0029484
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