Open AccessEmpirical estimation of the grades of hearing impairment among industrial workers based on new artificial neural networks and classical regression methods
Author(s) -
Maryam Farhadian,
Mohsen Aliabadi,
Ebrahim Darvishi
Publication year - 2015
Publication title -
the indian journal of occupational and environmental medicine/the indian journal of occupational and environmental medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 26
eISSN - 1998-3670
pISSN - 0973-2284
DOI - 10.4103/0019-5278.165337
Subject(s) - hearing loss , logistic regression , artificial neural network , audiometer , statistics , linear regression , regression analysis , mean squared error , computer science , regression , audiology , medicine , machine learning , mathematics , audiometry
Prediction models are used in a variety of medical domains, and they are frequently built from experience which constitutes data acquired from actual cases. This study aimed to analyze the potential of artificial neural networks and logistic regression techniques for estimation of hearing impairment among industrial workers.