Machine Learning Models Can Predict Tinnitus and Noise-Induced Hearing Loss.

Journal: Ear and hearing
Published Date: May 6, 2025

Abstract

OBJECTIVES: Despite the extensive use of machine learning (ML) models in health sciences for outcome prediction and condition classification, their application in differentiating various types of auditory disorders remains limited. This study aimed to address this gap by evaluating the efficacy of five ML models in distinguishing (a) individuals with tinnitus from those without tinnitus and (b) noise-induced hearing loss (NIHL) from age-related hearing loss (ARHL).

Authors

  • Zahra Jafari
    School of Communication Sciences and Disorders (SCSD), Dalhousie University, Halifax, Nova Scotia, Canada.
  • Ryan E Harari
    Harvard Data Science Initiative (HDSI), Harvard University, Cambridge, Massachusetts, USA.
  • Glenn Hole
    Audiology First, Lethbridge, Alberta, Canada.
  • Bryan E Kolb
    Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, Alberta, Canada.
  • Majid H Mohajerani
    Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, Alberta, Canada.

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