A robust model of the neuronal regulator of the lower urinary tract based on artificial neural networks

Neurocomputing

Volumn 71, Issue 4-6, 2008, Pages 743-754

  Maciá Pérez, Francisco ^a   García Chamizo, Juan Manuel ^a   Soriano Payá, Antonio ^a   Ruiz Fernández, Daniel ^a  

^a UNIVERSITY OF ALICANTE   (Spain)

Author keywords

Biological modeling; Multi agent systems; Neural networks; Process control

Indexed keywords

HEURISTIC METHODS; MULTI AGENT SYSTEMS; NEUROLOGY; NEURONS; PROCESS CONTROL;

BIOLOGICAL MODELING; LOWER URINARY TRACT; NEURONAL REGULATOR;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; ASSOCIATIVE MEMORY; BIOLOGICAL MODEL; COMPUTER SYSTEM; CONTROL SYSTEM; INFORMATION PROCESSING; PRIORITY JOURNAL; PROCESS CONTROL; TRAINING; URETHRA; URODYNAMICS;

EID: 38649123702     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2007.06.010     Document Type: Article

References (21)

1. Blok B.F.M., and Holstege G. The central control of micturition and continence: implications for urology. Brit. J. Urol. 83 (1999) 1-6
2. van Duin F., Rosier P.F., Bemelmans B.L., Wijkstra H., Debruyne F.M., and van Oosterom A. Comparison of different computer models of the neural control system of the lower urinary tract. Neurourol. Urodyn. 19 (2000) 289-310
3. van Duin F., Rosier P.F.W.M., Rijkhoff N.J.M., van Kerrebroeck P.E.V., Debruyne F.M.J., and y Wijkstra H. A computer model of the neural control of the lower urinary tract. Neurology and Urodynamics 17 (1998) 175-196
4. van Duyl W.A. A model for both passive and active properties of the urinary bladder tissue related to the bladder function. Neurourol Urodynamics 4 (1985) 275-283
5. Ferber J. Multi-Agent Systems. An Introduction to Distributed Artificial Intelligence (1999), Addison-Wesley, Reading, MA
6. García J.M., Soriano A., Maciá F., and Ruiz D. Simulation of the neuronal regulator of the lower urinary tract using a multiagent system. In: Goos G., Hartmanis J., and van Leeuwen J. (Eds). Artificial Neural Nets Problem Solving Methods. Lecture Notes in Computer Science 2687 (2003), Springer, Berlin Heidelberg New York pp. 591-598
7. Hill A.V. First and Last Experiments in Muscle Mechanics (1970), University Press, Cambridge
8. Hornik K., Stinchcombe M., and White H. Multilayer feedforward networks are universal approximators. Neural Networks 1 (1989) 359-366
9. Kinder M.V., Bastiaanssen E.H.C., Janknegt R.A., and Marani E. Neuronal circuitry of the lower urinary tract, central and peripheral neuronal control of the micturition cycle. Anat. Embryol. 192 (1995) 195-209
10. Kinder M.V., Bastiaanssen E.H.C., Janknegt R.A., and Marani E. The neuronal control of the lower urinary tract: a model of architecture and control mechanisms. Arch. Physiol. Biochem. 107 (1999) 203-222
11. Kondo A., Susset J., and Lefaivre J. Viscoelastic properties of bladder I. Mechanical model and its mathematical analysis. Investigative Urology 10 (1972) 154-162
12. Leoncini L., Manzini G., and Margara L. Parallel complexity of householder QR factorization. In: Díaz J., and Serna M.J. (Eds). Algorithms-ESA '96, Lecture Notes in Computer Science vol. 1136 (1996), Springer, Berlin 290-301
13. F. Maciá, Modelling of administration of heterogeneous of computer networks. System of regeneration of nodes of networks. PhD dissertation Dept. Comp. Tech. University of Alicante, Alicante, Spain. 2001.
14. Narendra K.S. Neural networks for control: theory and practice. Proceedings of IEEE 10 (1996) 1385-1402
15. Norgaard M. Neural Networks for Modelling and Control of Dynamic Systems (2000), Springer, Berlin
16. Ruiz D., García J.M., Maciá F., and Soriano A. Modelling the distributed control of the Lower Urinary tract using a multiagent system. Lecture notes in artificial intelligence vol. 3131 (2004), Springer, Berlin Heidelberg, New York pp. 104-114
17. a ed., (1995) 229-246.
18. A. Soriano, J.M. García, F. Ibarra, F. Maciá, Urodynamic model of the lower urinary tract. Proceedings of Computational Intelligence for Modelling, Control & Automation CIMCA'99, 1999, pp. 123-128.
19. Sotolongo J.R. Causes and treatment of neurogenic bladder dysfunction. In: Krane R.J., et al. (Ed). Clinical Urology (1994), J.B. Lippincott Company 558-568
20. Tewari A. Artificial intelligence and neural networks: concept, applications and future in urology. Brit. J. Urol. 80 (1997) 53-58
21. Zinner N.R., Ritter R.C., Sterling A.M., and Donker P.J. The physical basis of some urodynamic mesasurements. Journal of Urology 117 (1977) 682-689