Diagnosis of Middle Ear Diseases using Deep Learning Paradigm

Abstract

In recent years, research has focused on developing a deep learning network that could use images of the ear drum identify conditions in the middle ear. Automatic ear problem diagnosis in particular, can be helpful. Even when antibiotics are used to treat it, otitis media still drives hearing impairment, even loss of hearing in almost all age groups. The evaluation of the tympanic membrane and assessment of the potential value of the network during the diagnostic process constitute the initial examination for the diagnosis of ear sickness. The strategy for identifying middle ear disorders using several deep learning models is proposed in this paper. Deep neural learning aid in the analysis of ear condition may increase medical accessibility for persons without access to otolaryngologists by assisting non- specialists in recognizing otitis media. This deep learning network will be able to diagnose the middle ear problems more precisely and help doctors analyse images of the tympanic membrane.