Applications of Machine Learning in Meniere's Disease Assessment Based on Pure-Tone Audiometry.

Journal: Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
PMID: 39194410

Abstract

OBJECTIVE: To apply machine learning models based on air conduction thresholds of pure-tone audiometry for automatic diagnosis of Meniere's disease (MD) and prediction of endolymphatic hydrops (EH).

Authors

  • Xu Liu
    School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore. liuxu16@bjut.edu.cn.
  • Ping Guo
    School of Systems Science, Beijing Normal University, Beijing 100875, China. Electronic address: pguo@bnu.edu.cn.
  • Dan Wang
    Guangdong Pharmaceutical University Guangzhou Guangdong China.
  • Yue-Lin Hsieh
    Department of Otorhinolaryngology, Eye and ENT Hospital, ENT Institute, Fudan University, Shanghai, China.
  • Suming Shi
    Department of Otorhinolaryngology, Eye and ENT Hospital, ENT Institute, Fudan University, Shanghai, China.
  • Zhijian Dai
    School of Automation Engineering of University of Electronic and Technology of China, Chengdu, China.
  • Deping Wang
    Department of Otorhinolaryngology-Head and Neck Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
  • Hongzhe Li
    Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
  • Wuqing Wang
    Department of Otorhinolaryngology, Eye and ENT Hospital, ENT Institute, Fudan University, Shanghai, China.

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