The CNN model aided the study of the clinical value hidden in the implant images.

Journal: Journal of applied clinical medical physics
PMID: 37656066

Abstract

PURPOSE: This article aims to construct a new method to evaluate radiographic image identification results based on artificial intelligence, which can complement the limited vision of researchers when studying the effect of various factors on clinical implantation outcomes.

Authors

  • Xinxu Huang
    State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
  • Xingyu Chen
    Department of Infectious Diseases, Wenzhou Central Hospital, Wenzhou, China.
  • Xinnan Zhong
    State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
  • Taoran Tian
    State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.

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