Hearing Loss Prediction using Machine Learning Approaches: Contributions, Limitations and Issues

Hearing, one of the five basic human senses is the ability to perceive sounds and give meaning to them. Hearing loss is a significant health problem affecting children and adults and is growing exponentially. There is a lack of knowledge regarding hearing loss despite enough awareness, resulting in detection and treatment delays. The need for detection at an early stage is significant so that people can take necessary precautions given the limited options for treatment. This paper aims to survey machine learning-based hearing loss prediction. We investigate datasets, machine learning methods, and their outcomes. We also discuss the constraints, difficulties, and intended future works. Based on the results of this survey, we have a greater understanding of the problem's complexity, the obstacles to developing a better system, and the scope of the research, which has led us to concentrate our efforts in the future on analysing data from newborns, infants, and young children.