Diabetic retinopathy classification for supervised machine learning algorithms

Diabetic retinopathy classification for supervised machine learning algorithms

Abstract Background Artificial intelligence and automated technology were first reported more than 70 years ago and nowadays provide unprecedented diagnostic accuracy, screening capacity, risk stratification, and workflow optimization. Diabetic retinopathy is an important cause of preventable blindn...

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Bibliographic Details
Main Authors: Luis Filipe Nakayama, Lucas Zago Ribeiro, Mariana Batista Gonçalves, Daniel A. Ferraz, Helen Nazareth Veloso dos Santos, Fernando Korn Malerbi, Paulo Henrique Morales, Mauricio Maia, Caio Vinicius Saito Regatieri, Rubens Belfort Mattos
Format: Article
Language:English
Published: BMC 2022-01-01
Series:International Journal of Retina and Vitreous
Subjects:
Diabetic retinopathy classifications
Artificial intelligence
Datasets
Online Access:https://doi.org/10.1186/s40942-021-00352-2

Internet

https://doi.org/10.1186/s40942-021-00352-2

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