Investigating the use of a two-stage attention-aware convolutional neural network for the automated diagnosis of otitis media from tympanic membrane images: a prediction model development and validation study.

Journal: BMJ open
Published Date: Jan 21, 2021

Abstract

OBJECTIVES: This study investigated the usefulness and performance of a two-stage attention-aware convolutional neural network (CNN) for the automated diagnosis of otitis media from tympanic membrane (TM) images.

Authors

  • Yuexin Cai
    Department of Otolaryngology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong Province, China.
  • Jin-Gang Yu
    School of Automation Science and Engineering, South China University of Technology, China.
  • Yuebo Chen
    Department of Otolaryngology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong Province, China.
  • Chu Liu
    Department of Otolaryngology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong Province, China.
  • Lichao Xiao
    School of Automation Science and Engineering, South China University of Technology, China.
  • Emad M Grais
    Centre for Speech and Language Therapy and Hearing Science, Cardiff School of Sport and Health Sciences, Cardiff Metropolitan University, Cardiff, UK.
  • Fei Zhao
  • Liping Lan
    Department of Otolaryngology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong Province, China.
  • Shengxin Zeng
    Department of Otolaryngology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong Province, China.
  • Junbo Zeng
    Department of Otolaryngology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong Province, China.
  • Minjian Wu
    Department of Otolaryngology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong Province, China.
  • Yuejia Su
    Department of Otolaryngology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong Province, China.
  • Yuanqing Li
    Center for Brain Computer Interfaces and Brain Information Processing, South China University of Technology, Guangzhou, China.
  • Yiqing Zheng
    Department of Otolaryngology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, China; Institute of Hearing and Speech-Language Science, Sun Yat-sen University, China; Department of Hearing and Speech-Language Science, Xinhua College, Sun Yat-sen University, China. Electronic address: zhengyiq@mail.sysu.edu.cn.

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