Various Patient classification model using ABR data

Auditory brain response (ABR) is an auditory test developed in the 1970s that enables objective testing regardless of age. However, ABR has the disadvantage that analysis and reading are essential because it is complicated to inspect and requires trained inspectors. In this paper, we present a deep learning Keras sequential model and a VGG16 model that distinguish between deaf patients and normal people using ABR data and compare the performance and accuracy of the model. It is expected that a deep learning model that automatically distinguishes deaf patients from normal people will be applied in the future using the proposed model.