AIMC Topic: Otoscopy
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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.
Artificial intelligence to detect tympanic membrane perforations.
The Journal of laryngology and otology
Apr 2, 2020
OBJECTIVE: To explore the feasibility of constructing a proof-of-concept artificial intelligence algorithm to detect tympanic membrane perforations, for future application in under-resourced rural settings.
Building an Otoscopic screening prototype tool using deep learning.
Journal of otolaryngology - head & neck surgery = Le Journal d'oto-rhino-laryngologie et de chirurgie cervico-faciale
Nov 26, 2019
BACKGROUND: Otologic diseases are often difficult to diagnose accurately for primary care providers. Deep learning methods have been applied with great success in many areas of medicine, often outperforming well trained human observers. The aim of th...
Otoscopic diagnosis using computer vision: An automated machine learning approach.
The Laryngoscope
Sep 18, 2019
OBJECTIVE: Access to otolaryngology is limited by lengthy wait lists and lack of specialists, especially in rural and remote areas. The objective of this study was to use an automated machine learning approach to build a computer vision algorithm for...
Detecting tympanostomy tubes from otoscopic images via offline and online training.
Computers in biology and medicine
Apr 4, 2015
Tympanostomy tube placement has been commonly used nowadays as a surgical treatment for otitis media. Following the placement, regular scheduled follow-ups for checking the status of the tympanostomy tubes are important during the treatment. The comp...
Optimized fine-tuned ensemble classifier using Bayesian optimization for the detection of ear diseases.
Computers in biology and medicine
Jun 1, 2025
External and middle ear diseases are common disorders, especially in children, and can be examined using a digital otoscope. Hearing loss can result from delayed diagnosis and treatment which is subjective and error-prone depending on the expertise o...
Development and Validation of an Automated Classifier to Diagnose Acute Otitis Media in Children.
JAMA pediatrics
Apr 1, 2024
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 developed to recognize the presence of AOM with limited clinical applicati...
A Web-Based Deep Learning Model for Automated Diagnosis of Otoscopic Images.
Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology
Oct 1, 2021
OBJECTIVES: To develop a multiclass-classifier deep learning model and website for distinguishing tympanic membrane (TM) pathologies based on otoscopic images.
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