Using the Breeder genetic algorithm to optimize a multiple regression analysis model used in prediction of the mesiodistal width of unerupted teeth
Keywords:genetic algorithms, multiple regression equations, mixed dentition analysis, mesiodistal teeth size
AbstractFor the prediction of the unerupted canine and premolars mesiodistal size, have been proposed different variants of multiple linear regression equations (MLRE). These are based on the amount of the upper and lower permanent incisors with a tooth of the lateral support. Aim of present study was to develop a method for optimization of MLRE, using a genetic algorithm for determining a set of coefficients that minimizes the prediction error for the sum of permanent premolars and canines dimensions from a group of young people in an area Romania's central city represented by Sibiu. To test the proposed method, we used a multiple linear regression equation derived from the estimation method proposed by Mojers to which we adjusted regression coefficients using Breeder genetic algorithm proposed by Muhlenbein and Schlierkamp.Â A total of 92 children were selected with complete permanent teeth which had not clinically visible dental caries, proximal restorations or orthodontic treatment that requires the decrease of the mesiodistal size of teeth. For each of these models was made a hard dental stone which was then measured with a digital calliper, the instrument having an accuracy of 0.01 mm. To improve prediction equations, we divided data into training and validation sets. The Breeder algorithm, using the training set, will provide new values for regression coefficients and error term. The validation set was used to test the accuracy of the new proposed equations.
Moyers R. E - Handbook of orthodontics Chicago: Year Book Medical Publishers, 1988
Mühlenbein H, Schlierkamp-Voosen D-The science of breeding and its application to the breeder genetic algorithm, Evolutionary Computation, vol. 1, 1994, 335-360 http://dx.doi.org/10.1162/evco.19184.108.40.2065
Boboc A, Dibbets J - Prediction of the mesiodistal width of unerupted canines and premolars: a statistical approach, American Journal of Orthodontics and Dentofacial Ortopedics, 2010, vol 137(4);503-507 http://dx.doi.org/10.1016/j.ajodo.2008.04.031
Pancherez H, Schaffer C - Individual-based prediction of the supporting zones in the permanent dentition. A comparison of the Moyers method with a unitary prediction value. Journal Orofacial Orthopedic, 1999, 60(4); 227-2355. http://dx.doi.org/10.1007/BF01299781
Legovic M, Novosel A, Legovic A - Regression equation for determining mesiodistal crown diameters of canines and premolars, Angle Orthodontic, 2003, 73(3); 314-318
Legovic M, Novosel A, Skrinjaric T, Legovic A, Madi B, Ivancic N - A comparison of methods for predicting the size of unerupted permanent canines and premolars, European Journal Orthodontic, 2006, 28 (5); 485-490 http://dx.doi.org/10.1093/ejo/cjl015
Memon S, Fida M - Development of a prediction equation for the estimation of mandibilar canine and premolar widths from mandibular first permanent molar and incisor widths, European Journal Orthodontic, 2011, May 9[Epub ahead to print]
Alhaija Abu E S, Qudeimat M A - Mixed dentition space analysis in a Jordanian population: comparison of two methods, International Journal Paediatric Dentistry, 2006, 16(2); 104-110 http://dx.doi.org/10.1111/j.1365-263X.2006.00700.x
Aquino Melgaco C, Araujo de Sousa MT, Roules de Oliveira AC - Mandibular permanent first molar and incisor width as predictor of mandibular canine and premolar width, American Journal of Orthodontics and Dentofacial Orthopedics, 2007, 132(3); 340-345 http://dx.doi.org/10.1016/j.ajodo.2005.07.033
Moghimi S, Talebi M, Parisay I - Desing and implementation of a hybrid genetic algorithm and artificial neutral network system for predicting the sizes of unerupted canines and premolars, European Journal Orthodontic, Jun 2011
van der Merwe W S, Rossouw P, van Wyk Kotze T J, Trutero H - An adaptation of the Moyers mixed dentition space analysis for a Western Cape Caucasian population, The Journal of Dental Association South Africa, 1999, 46(9); 475-479
Melgaco CA, Araujo MT, Ruellas ACO - Applicability of three tooth size prediction methods for white Brazilians, Angle Orthodontic, 2006, 76(4); 644-649
Barnabe E, Flores-Mir C - Apparaising number and clinical significance of regression equations to predict unerupted canines and premolars, American Journal of Orthopedics and Dentofacial Orthopedics, 2004, 126(2); 228-230 http://dx.doi.org/10.1016/j.ajodo.2004.03.021
Barnabe E, Flores-Mir C - Are the lower incisors the best predictors for the unerupted canine and premolars sums? An analisis of a Peruvian sample, Angle Orthodontist, 2005, 75(2); 202-207
Martinelli FL, de Lima EM, Rocha R, de Sousa Araujo MT - Prediction of lower permanent canine and premolars width by correlation methods, Angle Orthodontist, 2005, 75(3); 805-808
Nourallah AW, Gesch D, Khordaji MN, Splieth C - New ecuations for predicting the size of unerupted canines and premolars in contemporary population, Angle Orthodontist, 2002, 72(3); 216-221
Bonetti GA, Verganti S,Zamarini M, Bonetti S - Mixed dentition space analisis for a northern Italian population: new regression equations for unerupted teeth, Progress in Ortodontics, 2011, 12(2); 94-96 http://dx.doi.org/10.1016/j.pio.2011.02.001
Philip NI, Prabhakar M, Arora D, Chopa S - Applicability of the Mojers mixed dentition probability tables and new prediction aids for a contemporary population in India, American Journal of Orthopedics and Dentofacial Orthopedics, 2011, 138(3); 339-345 http://dx.doi.org/10.1016/j.ajodo.2008.09.035
Stoica F., Simian D., Optimizing a New Nonlinear Reinforcement Scheme with Breeder genetic algorithm, Proceedings of the 11th International Conference on EVOLUTIONARY COMPUTING (EC'10),13-15 June 2010, IaÅŸi, Romania, ISSN: 1790-2769, ISBN: 978-960-474-194-6, pp. 273-278
Stoica F., Cacovean L.F., Using genetic algorithms and simulation as decision support in marketing strategies and long-term production planning, Proceedings of the 9th International Conference on SIMULATION, MODELLING AND OPTIMIZATION (SMO '09), Budapest Tech, Hungary, September 3-5 2009, ISSN: 1790-2769 ISBN: 978-960-474-113-7, pp 435-439
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