Fusing fine-tuned deep features for recognizing different tympanic membranes-Reference-Cited by-同舟云学术

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Fusing fine-tuned deep features for recognizing different tympanic membranes

Published:2020-01 Issue:1 Volume:40 Page:40-51
ISSN:0208-5216
Container-title:Biocybernetics and Biomedical Engineering
language:en
Short-container-title:Biocybernetics and Biomedical Engineering

Author:

Zafer Cömert^ORCID

Publisher

Elsevier BV

Subject

Biomedical Engineering

Reference53 articles.

1. Current management and referral patterns of pediatricians for acute otitis media;Shah-Becker;Int J Pediatr Otorhinolaryngol,2018

2. Emerging technologies for the diagnosis of otitis media;Marom;Otolaryngol Neck Surg,2019

3. Otitis media;Schilder;Nat Rev Dis Prim,2016

4. Diagnosis and management of acute otitis media;Pediatrics,2004

5. Optimising pain management in children with acute otitis media through a primary care-based multifaceted educational intervention: study protocol for a cluster randomised controlled trial;van Uum;Trials,2018

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1. Reimagining otitis media diagnosis: A fusion of nested U-Net segmentation with graph theory-inspired feature set;Array;2024-09

2. Development and Validation of an Automated Classifier to Diagnose Acute Otitis Media in Children;JAMA Pediatrics;2024-04-01

3. Identification of multiclass tympanic membranes by using deep feature transfer learning and hyperparameter optimization;Measurement;2024-04

4. An ensemble approach for classification of tympanic membrane conditions using soft voting classifier;Multimedia Tools and Applications;2024-02-22

5. Artificial Intelligence-Driven Advancements in Otitis Media Diagnosis: A Systematic Review;IEEE Access;2024

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