Evaluation of machine learning classifiers in keratoconus detection from orbscan II examinations

PURPOSE: To evaluate the performance of support vector machine, multi‐layer perceptron and radial basis function neural network as auxiliary tools to identify keratoconus from Orbscan II maps. METHODS: A total of 318 maps were selected and classified into four categories: normal (n = 172), astigmati...

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Detalles Bibliográficos
Autores principales: Souza, Murilo Barreto, Medeiros, Fabricio Witzel, Souza, Danilo Barreto, Garcia, Renato, Alves, Milton Ruiz
Formato: Texto
Lenguaje:English
Publicado: Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo 2010
Materias:
Clinical Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3020330/
https://www.ncbi.nlm.nih.gov/pubmed/21340208
http://dx.doi.org/10.1590/S1807-59322010001200002

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3020330/
https://www.ncbi.nlm.nih.gov/pubmed/21340208
http://dx.doi.org/10.1590/S1807-59322010001200002

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