OBJECTIVES: Pure-tone audiometry has been a staple of hearing assessments for decades. Many different procedures have been proposed for measuring thresholds with pure tones by systematically manipulating intensity one frequency at a time until a disc...
OBJECTIVES: To demonstrate the feasibility of developing machine learning models for the prediction of hearing impairment in humans exposed to complex non-Gaussian industrial noise.
OBJECTIVES: A confluence of recent developments in cloud computing, real-time web audio and machine learning psychometric function estimation has made wide dissemination of sophisticated turn-key audiometric assessments possible. The authors have com...
Diagnostic tests for hearing impairment not only determines the presence (or absence) of hearing loss, but also evaluates its degree and type, and provides physicians with essential data for future treatment and rehabilitation. Therefore, accurately ...
INTRODUCTION: Cochlear implants (CIs) are commonly used for the rehabilitation of profound bilateral hearing loss. However, patients with substantial residual acoustic hearing are potential CI candidates. Because of both improvements in technology an...
OBJECTIVE: To assess the accuracy and reliability of a machine learning (ML) algorithm for predicting the full audiograms of hearing-impaired children relative to the common approach (CA).