AIMC Topic: Otitis Media with Effusion
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Artificial Intelligence and Pediatric Otolaryngology.
Otolaryngologic clinics of North America
Jul 20, 2024
Artificial intelligence (AI) studies show how to program computers to simulate human intelligence and perform data interpretation, learning, and adaptive decision-making. Within pediatric otolaryngology, there is a growing body of evidence for the ro...
The effect of soft palate reconstruction with the da Vinci robot on middle ear function in children: an observational study.
International journal of oral and maxillofacial surgery
Mar 11, 2023
Cleft palate is associated with a high prevalence of middle ear dysfunction, even after palatal repair. The aim of this study was to evaluate the effects of robot-enhanced soft palate closure on middle ear functioning. This retrospective study compar...
"Human vs Machine" Validation of a Deep Learning Algorithm for Pediatric Middle Ear Infection Diagnosis.
Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Jan 27, 2023
OBJECTIVE: We compared the diagnostic performance of human clinicians with that of a neural network algorithm developed using a library of tympanic membrane images derived from children taken to the operating room with the intent of performing myring...
A deep learning approach to the diagnosis of atelectasis and attic retraction pocket in otitis media with effusion using otoscopic images.
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Oct 13, 2022
BACKGROUND: This study aimed to develop and validate a deep learning (DL) model to identify atelectasis and attic retraction pocket in cases of otitis media with effusion (OME) using multi-center otoscopic images.
Automated multi-class classification for prediction of tympanic membrane changes with deep learning models.
PloS one
Oct 10, 2022
BACKGROUNDS AND OBJECTIVE: Evaluating the tympanic membrane (TM) using an otoendoscope is the first and most important step in various clinical fields. Unfortunately, most lesions of TM have more than one diagnostic name. Therefore, we built a databa...
A Deep Learning Approach for Detecting Otitis Media From Wideband Tympanometry Measurements.
IEEE journal of biomedical and health informatics
Jul 1, 2022
OBJECTIVE: In this study, wepropose an automatic diagnostic algorithm for detecting otitis media based on wideband tympanometry measurements.
Automatic Prediction of Conductive Hearing Loss Using Video Pneumatic Otoscopy and Deep Learning Algorithm.
Ear and hearing
Mar 29, 2022
OBJECTIVES: Diseases of the middle ear can interfere with normal sound transmission, which results in conductive hearing loss. Since video pneumatic otoscopy (VPO) findings reveal not only the presence of middle ear effusions but also dynamic movemen...
Shortwave infrared otoscopy for diagnosis of middle ear effusions: a machine-learning-based approach.
Scientific reports
Jun 15, 2021
Otitis media, a common disease marked by the presence of fluid within the middle ear space, imparts a significant global health and economic burden. Identifying an effusion through the tympanic membrane is critical to diagnostic success but remains c...
Analysing wideband absorbance immittance in normal and ears with otitis media with effusion using machine learning.
Scientific reports
May 20, 2021
Wideband Absorbance Immittance (WAI) has been available for more than a decade, however its clinical use still faces the challenges of limited understanding and poor interpretation of WAI results. This study aimed to develop Machine Learning (ML) too...
Machine Learning for Accurate Intraoperative Pediatric Middle Ear Effusion Diagnosis.
Pediatrics
Mar 17, 2021
OBJECTIVES: Misdiagnosis of acute and chronic otitis media in children can result in significant consequences from either undertreatment or overtreatment. Our objective was to develop and train an artificial intelligence algorithm to accurately predi...
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