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Hearing loss is a common problem faced by humans, especially adults. The report stated that are most of the adult are affected by the Hearing impairment (HI) who is partially or fully disable from hearing. Machine learning (ML) techniques were used to apply to predict the HI with higher accuracy. The ML is the most advanced method that can make it possible to learn any kind of complex data and provide good results. Therefore the ML is used for HI prediction and also diagnose HI with better classification models. In this work, the review of ML-based HI predictions is presented and listed the performances of literature in terms of accuracy and time consumption. Further, this work provides a better ML method to solve the HI issues by summarising the literature, comparing between the ML methods and the performances are also offered in this work.
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