title: Retreatment Predictions in Odontology by means of CBR Systems.
abstract: The field of odontology requires an appropriate adjustment of treatments according to the circumstances of each patient. A follow-up treatment for a patient experiencing problems from a previous procedure such as endodontic therapy, for example, may not necessarily preclude the possibility of extraction. It is therefore necessary to investigate new solutions aimed at analyzing data and, with regard to the given values, determine whether dental retreatment is required. In this work, we present a decision support system which applies the case-based reasoning (CBR) paradigm, specifically designed to predict the practicality of performing or not performing a retreatment. Thus, the system uses previous experiences to provide new predictions, which is completely innovative in the field of odontology. The proposed prediction technique includes an innovative combination of methods that minimizes false negatives to the greatest possible extent. False negatives refer to a prediction favoring a retreatment when in fact it would be ineffective. The combination of methods is performed by applying an optimization problem to reduce incorrect classifications and takes into account different parameters, such as precision, recall, and statistical probabilities. The proposed system was tested in a real environment and the results obtained are promising.
authors.affiliation: Department of Estomatology II, Complutense University of Madrid, Plaza Ramón y Cajal, s/n, 28040 Madrid, Spain.
authors.forename: Livia
authors.initials: L
authors.lastname: Campo
authors.affiliation: Department of Estomatology II, Complutense University of Madrid, Plaza Ramón y Cajal, s/n, 28040 Madrid, Spain.
authors.forename: Ignacio J
authors.initials: IJ
authors.lastname: Aliaga
authors.affiliation: Biomedical Research Institute of Salamanca/BISITE Research Group, Calle Espejo, s/n, 37007 Salamanca, Spain.
authors.forename: Juan F
authors.identifier: 0000-0001-9461-7922
authors.initials: JF
authors.lastname: De Paz
authors.affiliation: Department of Estomatology II, Complutense University of Madrid, Plaza Ramón y Cajal, s/n, 28040 Madrid, Spain.
authors.forename: Alvaro Enrique
authors.initials: AE
authors.lastname: García
authors.affiliation: Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid, Campus Montegancedo, Boadilla del Monte, 28660 Madrid, Spain.
authors.forename: Javier
authors.identifier: 0000-0003-0824-4133
authors.initials: J
authors.lastname: Bajo
authors.affiliation: Biomedical Research Institute of Salamanca/BISITE Research Group, Calle Espejo, s/n, 37007 Salamanca, Spain.
authors.forename: Gabriel
authors.initials: G
authors.lastname: Villarubia
authors.affiliation: Biomedical Research Institute of Salamanca/BISITE Research Group, Calle Espejo, s/n, 37007 Salamanca, Spain; Osaka Institute of Technology, Osaka 535-8585, Japan.
authors.forename: Juan M
authors.initials: JM
authors.lastname: Corchado
mesh_terms: D019540:Area Under Curve; D016022:Case-Control Studies; D019465:Craniofacial Abnormalities / Q000175:diagnosis* / Q000628:therapy*; D003813:Dentistry; D006801:Humans; D011237:Predictive Value of Tests; D011336:Probability; D019233:Retreatment; D018709:Statistics, Nonparametric; D014076:Tooth Diseases / Q000175:diagnosis* / Q000628:therapy*