On the Use of Machine Learning for Classifying Auditory Brainstem Responses: A Scoping Review

Recent advances in machine learning have led to a surge of interest classification the auditory brainstem response. In this work, we conducted search PubMed, Google Scholar, SpringerLink, ScienceDirect, and Scopus databases, identified twelve studies that explored use classify response as complementary objective method (a) help clinicians better diagnose hearing impairment by discerning between healthy pathological waveforms, (b) present neural marker for potential applications aid tuning, (c) provide biometric discriminating subjects. A comparison presented review is not possible they used different test subjects, group sizes, stimuli, evaluated differently. Instead, result these will be their limitations well discussed. Overall, findings suggest ABR using promising tool assessing patients with loss, optimizing technologies tuning aids,