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Dental Age Estimation in East Asian Population with Least Squares Regression

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The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018) (AMLTA 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 723))

Abstract

The purpose of the study is to derive a machine learning method of estimating overall dental maturity or dental age to achieve higher accuracy than the former methods. We select 1697 orthopantomograms of 877 boys and 820 girls from Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, of which 1695 (875 boys and 820 girls) are used for estimating the dental age with the Demirjian’s method, Willem’s method and our method. Analysis of Variance (ANOVA) of randomized block design is performed to search for statistically significant differences between the chronological age and the dental age of three methods. Root-mean-square error (RMSE) is also performed in order to analyze the errors of the three methods. The adapted method is validated and results in more accurate dental age estimations in this population compared with Demirjian’s method and Willem’s method.

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Author information

Authors and Affiliations

  1. Department of General Dentistry, Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Jiang Tao & Jian Wang

  2. Shanghai Jiao Tong University, Shanghai, China

    Mufan Chen & Kai Xiao

  3. School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Lin Liu

  4. Cairo University, Giza, Egypt

    Aboul Ella Hassanien

Authors
  1. Jiang Tao
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  2. Mufan Chen
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  3. Jian Wang
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  4. Lin Liu
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  5. Aboul Ella Hassanien
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  6. Kai Xiao
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Corresponding author

Correspondence to Jiang Tao .

Editor information

Editors and Affiliations

  1. Faculty of Computers and Information, Information Technology Department, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Faculty of Computers and Information Sciences, Ain Shams University, Cairo, Egypt

    Mohamed F. Tolba

  3. Faculty of Computers and Information, Department of Computer Science and Engineering, Mansoura University, Dakahlia, Egypt

    Mohamed Elhoseny

  4. Arab Academy for Science, Technology and Maritime Transport (AASTMT), Dokki, Egypt

    Mohamed Mostafa

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Tao, J., Chen, M., Wang, J., Liu, L., Hassanien, A.E., Xiao, K. (2018). Dental Age Estimation in East Asian Population with Least Squares Regression. In: Hassanien, A., Tolba, M., Elhoseny, M., Mostafa, M. (eds) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018). AMLTA 2018. Advances in Intelligent Systems and Computing, vol 723. Springer, Cham. https://doi.org/10.1007/978-3-319-74690-6_64

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  • DOI: https://doi.org/10.1007/978-3-319-74690-6_64

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74689-0

  • Online ISBN: 978-3-319-74690-6

  • eBook Packages: EngineeringEngineering (R0)

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