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Improving Glaucoma Diagnosis Assembling Deep Networks and Voting Schemes.
Sánchez-Morales, Adrián; Morales-Sánchez, Juan; Kovalyk, Oleksandr; Verdú-Monedero, Rafael; Sancho-Gómez, José-Luis.
Afiliación
  • Sánchez-Morales A; Departamento de Tecnologías de la Información y las Comunicaciones, Campus Muralla del Mar, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain.
  • Morales-Sánchez J; Departamento de Tecnologías de la Información y las Comunicaciones, Campus Muralla del Mar, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain.
  • Kovalyk O; Departamento de Tecnologías de la Información y las Comunicaciones, Campus Muralla del Mar, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain.
  • Verdú-Monedero R; Departamento de Tecnologías de la Información y las Comunicaciones, Campus Muralla del Mar, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain.
  • Sancho-Gómez JL; Departamento de Tecnologías de la Información y las Comunicaciones, Campus Muralla del Mar, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain.
Diagnostics (Basel) ; 12(6)2022 Jun 02.
Article en En | MEDLINE | ID: mdl-35741192
Glaucoma is a group of eye conditions that damage the optic nerve, the health of which is vital for good eyesight. This damage is often caused by higher-than-normal pressure in the eye. In the past few years, the applications of artificial intelligence and data science have increased rapidly in medicine especially in imaging applications. In particular, deep learning tools have been successfully applied obtaining, in some cases, results superior to those obtained by humans. In this article, we present a soft novel ensemble model based on the K-NN algorithm, that combines the probability of class membership obtained by several deep learning models. In this research, three models of different nature (CNN, CapsNets and Convolutional Autoencoders) have been selected searching for diversity. The latent space of these models are combined using the local information provided by the true sample labels and the K-NN algorithm is applied to determine the final decision. The results obtained on two different datasets of retinal images show that the proposed ensemble model improves the diagnosis capabilities for both the individual models and the state-of-the-art results.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Diagnostics (Basel) Año: 2022 Tipo del documento: Article País de afiliación: España Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Diagnostics (Basel) Año: 2022 Tipo del documento: Article País de afiliación: España Pais de publicación: Suiza