Evaluation of transfer ensemble learning-based convolutional neural network models for the identification of chronic gingivitis from oral photographs.

Journal: BMC oral health
PMID: 39020332

Abstract

BACKGROUND: To evaluate the performances of several advanced deep convolutional neural network models (AlexNet, VGG, GoogLeNet, ResNet) based on ensemble learning for recognizing chronic gingivitis from screening oral images.

Authors

  • Wen Li
  • Enting Guo
    Division of Computer Science, The University of Aizu, Aizu, Japan.
  • Hong Zhao
    Key Laboratory of Medical Image Computing of Ministry of Education, Northeastern University, Shenyang, China.
  • Yuyang Li
    Department of Oral and Maxillofacial Surgery Hospital of Stomatology Jilin University Changchun China.
  • Leiying Miao
    Department of Endodontics, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing, China.
  • Chao Liu
    Anti-Drug Technology Center of Guangdong Province, National Anti-Drug Laboratory Guangdong Regional Center, Guangzhou 510230, China.
  • Weibin Sun
    Department of Periodontology, Nanjing Stomatological Hospital, Medical School of Nanjing University, Nanjing, China.

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