Int J Stomatol

Int J Stomatol ›› 2023, Vol. 50 ›› Issue (2): 146-151.doi: 10.7518/gjkq.2023033

• Artificial Intelligence • Previous Articles     Next Articles

Research progress of dental age evaluation based on machine learning methods

Tang Yueting1(),Dai Jiaqi2,Dong Wenxuan3,Wang Hu1,Guo Jixiang3,You Meng1()   

  1. 1.State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases & Dept. of Oral Medical Imaging, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
    2.Dept. of Oral Radiology, Sichuan Hospital of Stomatology, Chengdu 610015, China
    3.College of Computer Science, Sichuan University, Chengdu 610065, China
  • Received:2022-07-29 Revised:2022-11-10 Online:2023-03-01 Published:2023-03-14
  • Contact: Meng You E-mail:497315852@qq.com;youmeng@scu.edu.cn
  • Supported by:
    Exploration and Research and Development Project of West China Hospital of Stomatology, Sichuan University(LCYJ2019-9)

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Abstract:

Dental age is an important indicator of biological age and has essential application value in orthodontics, forensic dentistry, and criminal investigation. Traditional methods of dental age evaluation include atlas, scoring, and pulp cavity evaluation. These manual evaluation methods are relative cumbersome that their applications have been hampered. With the development of artificial intelligence technology and machine learning algorithms, intelligent evaluation of dental age have been gained more attention in recent years. This paper aims to provide a reference for the future research and application of dental age evaluation, summarize traditional and machine learning methods, and demonstrate the benefits and limitations of the existing approaches that are used in this topic.

Key words: dental age, dental age assessment, machine learning, artificial intelligence

CLC Number: 

  • R 780

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