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Mixed dentition analysis using a multivariate approach
다변량 기법을 이용한 혼합치열기 분석법

Cited 4 time in Web of Science Cited 4 time in Scopus
Issue Date
2009-04
Publisher
KOREAN ASSOC ORTHODONTISTS
Citation
KOREAN JOURNAL OF ORTHODONTICS, Vol.39, No.2, pp.112-119
Keywords
Tooth size predictionCluster analysisDiscriminant analysisMultiple regression
Abstract
Objective: To develop a mixed dentition analysis method in consideration of the normal variation of tooth sizes. Methods: According to the tooth-size of the maxillary central incisor, maxillary 1st molar, mandibular central incisor, mandibular lateral incisor, and mandibular 1st molar, 307 normal occlusion subjects were clustered into the smaller and larger tooth-size groups. Multiple regression analyses were then performed to predict the sizes of the canine and premolars; for the 2 groups and both genders separately. For a cross validation dataset, 504 malocclusion patients were assigned into the 2 groups. Then multiple regression equations were applied. Results: Our results show that the maximum errors of the predicted space for the canine, 1st and 2nd premolars were 0.71 and 0.82 mm residual standard deviation for the normal occlusion and malocclusion groups, respectively. For malocclusion patients, the prediction errors did not imply a statistically significant difference depending on the types of malocclusion nor the types of tooth-size groups. The frequency of prediction error more than 1 mm and 2 mm were 17.3% and 1.8%, respectively. The overall prediction accuracy was dramatically improved in this study compared to that of previous studies. Conclusions: The computer aided calculation method used in this study appeared to be more efficient. (Korean J Orthod 2009;39(2):112-119)
ISSN
1225-5610
Language
Korean
URI
https://hdl.handle.net/10371/80485
DOI
https://doi.org/10.4041/kjod.2009.39.2.112
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College of Dentistry/School of Dentistry (치과대학/치의학대학원)Dept. of Dentistry (치의학과)Journal Papers (저널논문_치의학과)
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