Objectives In this study, we propose a diagnostic model for automatic detection of otitis
media based on combined input of otoscopy images and wideband tympanometry …

Objective: In this study, wepropose an automatic diagnostic algorithm for detecting otitis
media based on wideband tympanometry measurements. Methods: We develop a …

In this study, we propose an automatic diagnostic algorithm for detecting otitis media based
on otoscopy images of the tympanic membrane. A total of 1336 images were assessed by a …

Backgrounds and objective Evaluating the tympanic membrane (TM) using an
otoendoscope is the first and most important step in various clinical fields. Unfortunately …

Objectives Otitis media is a common infection worldwide. Owing to the limited number of ear
specialists and rapid development of telemedicine, several trials have been conducted to …

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 …

Chronic otitis media is characterized by recurrent infections, leading to serious
complications, such as meningitis, facial palsy, and skull base osteomyelitis. Therefore …

Background: The integration of artificial intelligence (AI), particularly deep learning models,
has transformed the landscape of medical technology, especially in the field of diagnosis …

Background: Otitis media includes several common inflammatory conditions of the middle
ear that can have severe complications if left untreated. Correctly identifying otitis media can …

Otosclerosis is a common disease of the middle ear leading to stapedial fixation. Its rapid
and non-invasive diagnosis could be achieved through wideband tympanometry (WBT), but …