Classification of Diabetic Retinopathy using Machine Learning

Pérez Conde, Pilar; De la Calleja Mora, Jorge; Medina Nieto, María Auxilio; Benitez Ruiz, Antonio

dc.contributor	JORGE DE LA CALLEJA MORA;102624	es
dc.contributor.advisor	De la Calleja Mora, Jorge
dc.contributor.author	Pérez Conde, Pilar
dc.contributor.author	De la Calleja Mora, Jorge
dc.contributor.author	Medina Nieto, María Auxilio
dc.contributor.author	Benitez Ruiz, Antonio
dc.creator	GUDELIA PILAR PEREZ CONDE;375708	es
dc.date.accessioned	2018-06-29T05:59:53Z
dc.date.available	2018-06-29T05:59:53Z
dc.date.issued	2012-01-30
dc.identifier.citation	Pérez C. P., De la Calleja M. J., Medina N. M. A., Benitez R. A. 2012. Classification of Diabetic Retinopathy using Machine Learning. Universidad Politécnica de Puebla. Revista Visión Politécnica. Número 1.	es
dc.identifier.uri	http://repositorio.uppuebla.edu.mx:8080/xmlui/handle/123456789/204
dc.description	This paper presents a method to classify diabetic retinopathy using fundus images. In our study we categorize the disease into two classes: diabetic retinopathy non-proliferative and diabetic retinopathy proliferative. The method reduces the dimensionality of the images and find features using the statistical method of principal component analysis (PCA). Then, we classify the images using decision trees, the naive Bayes classifier, neural networks, k-nearest neighbors and support vector machines. The experimental results show that the naive Bayes classifier obtains the best results with 73.4% of accuracy using a data set of 151 images and testing with different resolutions.	es
dc.description.statementofresponsibility	Público en general	es
dc.language	Inglés	es
dc.publisher	UNIVERSIDAD POLITÉCNICA DE PUEBLA	es
dc.relation	Versión del autor	es
dc.relation.ispartof	REPOSITORIO NACIONAL CONACYT	es
dc.rights	Acceso Abierto	es
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0	es
dc.subject	Medical Image Analysis, Machine Learning, Principal Analysis Component, Diabetic Retinopathy	es
dc.subject.classification	INGENIERÍA Y TECNOLOGÍA	es
dc.title	Classification of Diabetic Retinopathy using Machine Learning	es
dc.type	Artículo	es