Advertisement

Case-Based Reasoning to Classify Endodontic Retreatments

  • Livia CampoEmail author
  • Vicente Vera
  • Enrique Garcia
  • Juan F. De Paz
  • Juan M. Corchado
Conference paper
  • 781 Downloads
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 154)

Abstract

Within the field of odontology, an analysis of the probability of success of endodontic retreatment facilitates the diagnostic and decision-making process of medical personnel. This study presents a case-based reasoning system that predicts the probability of success and failure of retreatments to avoid extraction. Different classifiers were applied during the reuse phase of the case-based reasoning process. The system was tested on a set of patients who received retreatments, and a set of variables considered to be of particular interest, were selected.

Keywords

case-based reasoning classification odontology 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Chugal, N.M., Clive, J.M., Spangberg, L.S.: A prognostic model for assessment of the outcome of endodontic treatment: Effect of biologic and diagnostic variables. Oral Surg. Oral Med. Oral Pathol. Oral Radiol. Endod. 91(3), 342–352 (2001)CrossRefGoogle Scholar
  2. 2.
    Givol, N., et al.: Risk management in endodontics. J. Endod. 36(6), 982–984 Google Scholar
  3. 3.
    Song, M., et al.: Prognostic factors for clinical outcomes in endodontic microsurgery: a retrospective study. J. Endod. 37(7), 927–933 Google Scholar
  4. 4.
    Kolodner, J.: Case-Based Reasoning. Morgan Kaufmann (1993)Google Scholar
  5. 5.
    Friedman, N., Geiger, D., Goldszmidt, M.: Bayesian Network Classifiers. Machine Learning 29, 131–163 (1997)zbMATHCrossRefGoogle Scholar
  6. 6.
    Castro, J.L., Navarro, M., Sánchez, J.M., Zurita, J.M.: Loss and gain functions for CBR retrieval. Information Science 179(11), 1738–1750 (2009)CrossRefGoogle Scholar
  7. 7.
    Joyanes, L., et al.: Knowledge Management. University of Paisley, Salamanca (2001)Google Scholar
  8. 8.
    Jurisica, I., Glasgow, J.: Applications of case-based reasoning in molecular biology. Artificial Intelligence Magazine 25(1), 85–95 (2004)Google Scholar
  9. 9.
    Canalda, C., Brau, E.: Endodoncia: técnicas clínicas y bases científicas, vol. 2. Masson, Barcelona (2006)Google Scholar
  10. 10.
    Casanellas, J.M.: Restauración del Diente Endodonciado, 1st edn. Pues, Madrid (2006)Google Scholar
  11. 11.
    Kruskal, W., Wallis, W.: Use of ranks in one-criterion variance analysis. Journal of American Statistics Association (1952)Google Scholar
  12. 12.
    Kenney, J.F., Keeping, E.S.: Mathematics of Statistics, Pt. 2, 2nd edn. Van Nostrand, Princeton (1951)Google Scholar
  13. 13.
    Martín Andrés, A., Silva Mato, A.: Optimal correction for continuity and conditions for validity in the unconditional chi-squared test. Computational Statistics & Data Analysis 26(1), 609–626 (1996)CrossRefGoogle Scholar
  14. 14.
    Himmetoglu, O., Tiras, M.B., Gursoy, R., Karabacak, O., Sahin, I., Onan, A.: The incidence of congenital malformations in a Turkish population. International Journal of Gynecology & Obstetrics 55(2), 117–121 (1996)CrossRefGoogle Scholar
  15. 15.
    Shaul, D.B., Scheer, B., Rokhsar, S., Jones, V.A., Chan, L.S., Boody, B.A., Malogolowkin, M.H., Mason, W.H.: Risk Factors for Early Infection of Central Venous Catheters in Pediatric Patients. Journal of the American College of Surgeons 186(6), 654–658 (1998)CrossRefGoogle Scholar
  16. 16.
    Yang, X., Huang, Y., Crowson, M., Li, J., Maitland, M.L., Lussier, Y.A.: Kinase inhibition-related adverse events predicted from in vitro kinome and clinical trial data.  43(3), 376–384 (2010)Google Scholar
  17. 17.
    Nilsson, B.: A compression algorithm for pre-simulated MonteCarlop-value functions: Application to the ontological analysis of microarray studies. Pattern Recognition Letters 29(6), 768–772 (2008)MathSciNetCrossRefGoogle Scholar
  18. 18.
    John, M., Priebe, C.E.: A data-adaptive methodology for finding an optimal weighted generalized Mann–Whitney–Wilcoxon statistic. Computational Statistics & Data Analysis 51(9), 4337–4353 (2007)MathSciNetzbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Livia Campo
    • 1
    Email author
  • Vicente Vera
    • 1
  • Enrique Garcia
    • 1
  • Juan F. De Paz
    • 2
  • Juan M. Corchado
    • 2
  1. 1.Department of Estomatology IIComplutense University of MadridMadridSpain
  2. 2.Department of Computer Science and AutomationUniversity of SalamancaSalamancaSpain

Personalised recommendations