Deep Learning for Classification of Pediatric Otitis Media.

Journal: The Laryngoscope
PMID: 33369754

Abstract

OBJECTIVES/HYPOTHESIS: To create a new strategy for monitoring pediatric otitis media (OM), we developed a brief, reliable, and objective method for automated classification using convolutional neural networks (CNNs) with images from otoscope.

Authors

  • Zebin Wu
    Department of Otolaryngology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
  • Zheqi Lin
    Department of R&D, Shenzhen Accurate Technology Co., Ltd, Shenzhen, China.
  • Lan Li
    Department of Otolaryngology, Shenzhen Children's Hospital, Shenzhen, China.
  • Hongguang Pan
    Department of Otolaryngology, Shenzhen Children's Hospital, Shenzhen, China.
  • Guowei Chen
    MADIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, People's Republic of China.
  • Yuqing Fu
    Department of Otolaryngology, Shenzhen Children's Hospital, Shenzhen, China.
  • Qianhui Qiu
    Department of Otolaryngology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.

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