A Trust-Based Methodology to Evaluate Deep Learning Models for Automatic Diagnosis of Ocular Toxoplasmosis from Fundus Images

A Trust-Based Methodology to Evaluate Deep Learning Models for Automatic Diagnosis of Ocular Toxoplasmosis from Fundus Images

In the automatic diagnosis of ocular toxoplasmosis (OT), Deep Learning (DL) has arisen as a powerful and promising approach for diagnosis. However, despite the good performance of the models, decision rules should be interpretable to elicit trust from the medical community. Therefore, the developmen...

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Bibliographic Details
Main Authors: Rodrigo Parra, Verena Ojeda, Jose Luis Vázquez Noguera, Miguel García-Torres, Julio César Mello-Román, Cynthia Villalba, Jacques Facon, Federico Divina, Olivia Cardozo, Verónica Elisa Castillo, Ingrid Castro Matto
Format: article
Language:EN
Published: MDPI AG 2021
Subjects:
deep learning
ocular toxoplasmosis
machine learning interpretability
trust
Medicine (General)
R5-920
Online Access:https://doaj.org/article/e9222ee88e094a61ab31e5560289cf84
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https://doaj.org/article/e9222ee88e094a61ab31e5560289cf84

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