Machine learning applications in hearing loss evaluation: A comprehensive review

To ascertain the likely ailment of a patient, physicians depend on their gut feelings, past experiences, and a fundamentally suggestive or symptomatic attitude. In contrast, other patients who need care may have to wait longer if the consultation takes longer than expected due to the many steps involved in problem identification and lengthy methods. As a result, those patients may feel increased stress and anxiety. Currently, one in five individuals’ experiences deafness, a figure projected to rise to one in four by 2050. A correct diagnosis is the first step in treating hearing loss. Due to the limited availability of audiologists, self-administered digital hearing tests must rely more on automated methods. The goal of this study is to assess how well automated and machine learning methods perform in assessing the severity of hearing loss.