Objective To update the literature and provide a systematic review of image‐based artificial
intelligence (AI) applications in otolaryngology, highlight its advances, and propose future …

Objectives To identify and review key research advances from the literature published
between 2019 and 2023 on the diagnosis and microbiology of otitis media (OM) including …

Examining otoscopic images for ear diseases is necessary when the clinical diagnosis of
ear diseases extracted from the knowledge of otolaryngologists is limited. Improved …

A common infectious disease, otitis media (OM) has a low rate of early diagnosis, which
significantly increases the difficulty of treating the disease and the likelihood of serious …

To evaluate the generalizability of artificial intelligence (AI) algorithms that use deep
learning methods to identify middle ear disease from otoscopic images, between internal to …

There are many examples of remote technologies that are clinically effective and provide
numerous benefits to adults with hearing loss. Despite this, the uptake of remote …

Middle ear health is a process that generally depends on eardrum health. Middle ear
disorders are more common during childhood. Permanent damage may occur in bacterial or …

The COVID-19 pandemic necessitated the development of accurate diagnostics in order to
control and minimize viral propagation; however, accurate and remote means of COVID-19 …

As with other subspecialities, remote otoscopy commonly regarded as telehealth is being
studied as a new approach for diagnosis of middle ear diseases. As in covid-19 pandemic …

The most common middle ear diseases are otitis media with effusion (OME), acute otitis
media (AOM) and chronic suppurative otitis media (CSOM)). Diagnosing middle ear disease …