Risk analysis of noise-induced hearing loss of workers in the automobile manufacturing industries based on back-propagation neural network model: a cross-sectional study in Han Chinese population.

Journal: BMJ open
PMID:

Abstract

OBJECTIVES: This study aims to predict the risk of noise-induced hearing loss (NIHL) through a back-propagation neural network (BPNN) model. It provides an early, simple and accurate prediction method for NIHL.

Authors

  • Yanmei Ruan
    Key Laboratory of Occupational Environment and Health, Guangzhou Twelfth People's Hospital, Guangzhou, China.
  • Guanhao Huang
    Department of Health care, BaiYun Women and Children's Hospital and Health Institute, Guangzhou, China.
  • Jinwei Zhang
    Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA; Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA.
  • Shiqi Mai
    Key Laboratory of Occupational Environment and Health, Guangzhou Twelfth People's Hospital, Guangzhou, China.
  • Chunrong Gu
    Department of anesthesia, People's Liberation Army Southern Theater Air Force Hospital, Guangzhou, China.
  • Xing Rong
    Key Laboratory of Occupational Environment and Health, Guangzhou Twelfth People's Hospital, Guangzhou, China.
  • Lili Huang
    Department of Endocrinology, Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, China.
  • Wenfeng Zeng
    Key Laboratory of Occupational Environment and Health, Guangzhou Twelfth People's Hospital, Guangzhou, China.
  • Zhi Wang
    Department of Pharmacy, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China.