AIMC Topic: Otoscopes

Clear Filters Showing 1 to 4 of 4 articles

Deep learning algorithm classification of tympanostomy tube images from a heterogenous pediatric population.

International journal of pediatric otorhinolaryngology Mar 13, 2025
IMPORTANCE: The ability to augment routine post-operative tube check appointments with at-home digital otoscopes and deep learning AI could improve health care access as well as reduce financial and time burden on families.
Child Middle Ear Ventilation Child, Preschool Otoscopy Otoscopes Female Tympanic Membrane Male Ear Canal Infant Deep Learning Algorithms Prospective Studies Humans
View on PubMed DOI

Pediatric tympanostomy tube assessment via deep learning.

American journal of otolaryngology Apr 28, 2024
PURPOSE: Tympanostomy tube (TT) placement is the most frequently performed ambulatory surgery in children under 15. After the procedure it is recommended that patients follow up regularly for "tube checks" until TT extrusion. Such visits incur direct...
Child, Preschool Child Pilot Projects Otoscopy Otoscopes Middle Ear Ventilation Tympanic Membrane Female Male Infant Deep Learning Algorithms Prospective Studies Humans
View on PubMed DOI

AI Model Versus Clinician Otoscopy in the Operative Setting for Otitis Media Diagnosis.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery Oct 11, 2023
Prior work has demonstrated improved accuracy in otitis media diagnosis based on otoscopy using artificial intelligence (AI)-based approaches compared to clinician evaluation. However, this difference in accuracy has not been shown in a setting resem...
Humans Artificial Intelligence Machine Learning Female Child Otitis Media Otoscopy Infant Otoscopes Male Child, Preschool
View on PubMed DOI

Deep Learning for Classification of Pediatric Otitis Media.

The Laryngoscope Dec 28, 2020
OBJECTIVES/HYPOTHESIS: To create a new strategy for monitoring pediatric otitis media (OM), we developed a brief, reliable, and objective method for automated classification using convolutional neural networks (CNNs) with images from otoscope.
Adolescent Child, Preschool Deep Learning Otoscopy Image Interpretation, Computer-Assisted Diagnostic Self Evaluation Otoscopes Infant, Newborn Otitis Media Prospective Studies Child Humans Male Reproducibility of Results Female Smartphone Infant
View on PubMed DOI
Popular Topics
Recent Journals