Background Students usually encounter stress throughout their academic path. Ongoing
stressors may lead to chronic stress, adversely affecting their physical and mental well …

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

Introduction Acute otitis media (AOM) affects most (80%) children by 5 years of age and is
the most common reason children are prescribed antibiotics. The epidemiology of AOM has …

Importance Acute otitis media (AOM) is a frequently diagnosed illness in children, yet the
accuracy of diagnosis has been consistently low. Multiple neural networks have been …

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 …

A machine learning platform operated without coding knowledge (Teachable machine®)
has been introduced. The aims of the present study were to assess the performance of the …

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 …

Artificial intelligence (AI) has the potential to improve the surgical treatment of patients with
head and neck cancer. AI algorithms can analyse a wide range of data, including images …

Introduction This study introduces a digital assessment tool for asynchronous and remote
ear-nose-and-throat (ENT) specialist assessment screening for complicated hearing loss …

Introduction Telehealth programs are important to deliver otolaryngology services for
Aboriginal and Torres Strait Islander children living in rural and remote areas, where …