title: Modelling the longevity of dental restorations by means of a CBR system.
abstract: The lifespan of dental restorations is limited. Longevity depends on the material used and the different characteristics of the dental piece. However, it is not always the case that the best and longest lasting material is used since patients may prefer different treatments according to how noticeable the material is. Over the last 100 years, the most commonly used material has been silver amalgam, which, while very durable, is somewhat aesthetically displeasing. Our study is based on the collection of data from the charts, notes, and radiographic information of restorative treatments performed by Dr. Vera in 1993, the analysis of the information by computer artificial intelligence to determine the most appropriate restoration, and the monitoring of the evolution of the dental restoration. The data will be treated confidentially according to the Organic Law 15/1999 on 13 December on the Protection of Personal Data. This paper also presents a clustering technique capable of identifying the most significant cases with which to instantiate the case-base. In order to classify the cases, a mixture of experts is used which incorporates a Bayesian network and a multilayer perceptron; the combination of both classifiers is performed with a neural network.
authors: Department of Conservative Dentistry, Complutense University of Madrid, Plaza Ramón y Cajal, s/n, 28040 Madrid, Spain.
authors: Ignacio J
authors: IJ
authors: Aliaga
authors: Department of Conservative Dentistry, Complutense University of Madrid, Plaza Ramón y Cajal, s/n, 28040 Madrid, Spain.
authors: Vicente
authors: V
authors: Vera
authors: Department of Computer Science and Automation, University of Salamanca, Plaza de la Merced, s/n, 37008 Salamanca, Spain.
authors: Juan F
authors: 0000-0001-9461-7922
authors: JF
authors: De Paz
authors: Department of Conservative Dentistry, Complutense University of Madrid, Plaza Ramón y Cajal, s/n, 28040 Madrid, Spain.
authors: Alvaro E
authors: AE
authors: García
authors: Artificial Intelligence and Bioinformatics Research Group, Faculty of Computing, Universiti Teknologi Malaysia (UTM), 81310 Skudai, Johor, Malaysia.
authors: Mohd Saberi
authors: 0000-0002-1079-4559
authors: MS
authors: Mohamad
mesh_terms: D001499:Bayes Theorem; D003793:Dental Restoration, Permanent; D006801:Humans; D008954:Models, Biological; D016571:Neural Networks, Computer