Screening Patients with Sensorineural Hearing Loss for Vestibular Schwannoma Using a Bayesian Classifier

Abstract

Background: Selecting patients with asymmetrical sensorineural hearing loss for further investigation continues to pose clinical and medicolegal challenges, given the disparity between the number of symptomatic patients and the low incidence of vestibular schwannoma (VS) as the underlying cause. We developed and validated a diagnostic model using Gaussian Process Ordinal Regression, a generalization of neural networks, for detecting vestibular schwannomas from clinical and audiological data, and compared its performance with existing audiological screening protocols.