Background Otitis media is one of the most common childhood diseases worldwide, but
because of lack of doctors and health personnel in developing countries it is often …

Otolaryngological diagnoses, such as otitis media, are traditionally performed using
endoscopy, wherein diagnostic accuracy can be subjective and vary among clinicians. The …

Background Otitis media (OM) is the infection and inflammation of the mucous membrane
covering the Eustachian with the airy cavities of the middle ear and temporal bone. OM is …

Background: OM is a public health issue that occurs commonly in pediatric population.
Caring for OM may incur significant indirect cost that stems mainly from loss of school or …

Objectives This study investigated the usefulness and performance of a two-stage attention-
aware convolutional neural network (CNN) for the automated diagnosis of otitis media from …

We propose a novel automated algorithm for classifying diagnostic categories of otitis
media: acute otitis media, otitis media with effusion, and no effusion. Acute otitis media …

Otitis media (OM) is a term used to describe the inflammation of the middle ear. The clinical
inspection of the tympanic membrane is conducted visually by experts. Visual inspection …

Objectives To summarise the accuracy of artificial intelligence (AI) computer vision
algorithms to classify ear disease from otoscopy. Design Systematic review and meta …

Otitis media is one of the most common childhood illnesses. Access to ear specialists and
specialist equipment is rudimentary in many third world countries, and general practitioners …

Objective: To develop an artificial intelligence image classification algorithm to triage
otoscopic images from rural and remote Australian Aboriginal and Torres Strait Islander …