Computer-aided diagnosis of external and middle ear conditions: A machine learning approach.
In medicine, a misdiagnosis or the absence of specialists can affect the patient's health, leading to unnecessary tests and increasing the costs of healthcare. In particular, the lack of specialists in otolaryngology in third world countries forces patients to seek medical attention from genera...
Main Authors: | Michelle Viscaino, Juan C Maass, Paul H Delano, Mariela Torrente, Carlos Stott, Fernando Auat Cheein |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2020-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0229226 |
Similar Items
-
Color Dependence Analysis in a CNN-Based Computer-Aided Diagnosis System for Middle and External Ear Diseases
by: Michelle Viscaino, et al.
Published: (2022-04-01) -
Computer-Aided Ear Diagnosis System Based on CNN-LSTM Hybrid Learning Framework for Video Otoscopy Examination
by: Michelle Viscaino, et al.
Published: (2021-01-01) -
Covariance-Based Measurement Selection Criterion for Gaussian-Based Algorithms
by: Fernando A. Auat Cheein
Published: (2013-01-01) -
The Middle Ear Microbiota in Healthy Dogs Is Similar to That of the External Ear Canal
by: Caroline Leonard, et al.
Published: (2023-03-01) -
Conditional Random Field Features and Structure Assessment for Digital Terrain Modeling
by: Tito Arevalo-Ramirez, et al.
Published: (2021-01-01)