A machine learning screening model for identifying the risk of high-frequency hearing impairment in a general population.

Journal: BMC public health
Published Date: Apr 25, 2024

Abstract

BACKGROUND: Hearing impairment (HI) has become a major public health issue in China. Currently, due to the limitations of primary health care, the gold standard for HI diagnosis (pure-tone hearing test) is not suitable for large-scale use in community settings. Therefore, the purpose of this study was to develop a cost-effective HI screening model for the general population using machine learning (ML) methods and data gathered from community-based scenarios, aiming to help improve the hearing-related health outcomes of community residents.

Authors

  • Yi Wang
    Department of Neurology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.
  • Xinmeng Yao
    Department of Epidemiology and Biostatistics, School of Public Health, Hangzhou Normal University, Hangzhou, 311121, Zhejiang, China.
  • DaHui Wang
    School of Systems Science and State Key Lab of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China. wangdh@bnu.edu.cn.
  • Chengyin Ye
    Department of Health Management, Hangzhou Normal University, Hangzhou, China.
  • Liangwen Xu
    Department of Epidemiology and Biostatistics, School of Public Health, Hangzhou Normal University, Hangzhou, 311121, Zhejiang, China. 20021403@hznu.edu.cn.

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