Predicting the hearing outcome in sudden sensorineural hearing loss via machine learning models.

Journal: Clinical otolaryngology : official journal of ENT-UK ; official journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery
Published Date: Jun 1, 2018

Abstract

OBJECTIVE: Sudden sensorineural hearing loss (SSHL) is a multifactorial disorder with high heterogeneity, thus the outcomes vary widely. This study aimed to develop predictive models based on four machine learning methods for SSHL, identifying the best performer for clinical application.

Authors

  • D Bing
    Department of Otolaryngology-Head and Neck Surgery, Institute of Otolaryngology, Chinese PLA General Hospital, Beijing, China.
  • J Ying
    Medical Support Center, Chinese PLA General Hospital, Beijing, China.
  • J Miao
    Keele campus, York University, Toronto, Canada.
  • L Lan
    Department of Otolaryngology-Head and Neck Surgery, Institute of Otolaryngology, Chinese PLA General Hospital, Beijing, China.
  • D Wang
    Department of Otolaryngology-Head and Neck Surgery, Institute of Otolaryngology, Chinese PLA General Hospital, Beijing, China.
  • L Zhao
  • Z Yin
    Department of Otolaryngology-Head and Neck Surgery, Institute of Otolaryngology, Chinese PLA General Hospital, Beijing, China.
  • L Yu
    Department of Otolaryngology-Head and Neck Surgery, Institute of Otolaryngology, Chinese PLA General Hospital, Beijing, China.
  • J Guan
    Department of Otolaryngology-Head and Neck Surgery, Institute of Otolaryngology, Chinese PLA General Hospital, Beijing, China.
  • Q Wang
    Jiangsu Institute of Poultry Sciences, Yangzhou 225125, China.

Keywords

External Resources

Popular Topics
Recent Journals