Research on the Characteristics of Food Impaction with Tight Proximal Contacts Based on Deep Learning.

Journal: Computational and mathematical methods in medicine
PMID: 34777558

Abstract

OBJECTIVE: Based on deep learning, the characteristics of food impaction with tight proximal contacts were studied to guide the subsequent clinical treatment of occlusal adjustment. At the same time, digital model building, software measurement, and statistical correlation analysis were used to explore the cause of tooth impaction and to provide evidence for clinical treatment.

Authors

  • Yitong Cheng
    Department of Prosthodontics, Shanxi Medical University School and Hospital of Stomatology, China.
  • Zhijiang Wang
    Shanxi Provincial Key Laboratory of Biomedical Imaging and Imaging Big Data, College of Big Data, North University of China, China.
  • Yue Shi
    Department of Clinical Laboratory Medicine Center, Inner Mongolia Autonomous Region People's Hospital, Hohhot, Inner Mongolia, China.
  • Qiaoling Guo
    Department of Prosthodontics, Shanxi Medical University School and Hospital of Stomatology, China.
  • Qian Li
    Emergency and Critical Care Center, Department of Emergency Medicine, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang, China.
  • Rui Chai
    Shanxi Provincial Key Laboratory of Biomedical Imaging and Imaging Big Data, College of Big Data, North University of China, China.
  • Feng Wu
    Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China.

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