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Incremental gaussian discriminant analysis based on graybill and deal weighted combination of estimators for brain tumour diagnosis

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Incremental gaussian discriminant analysis based on graybill and deal weighted combination of estimators for brain tumour diagnosis

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Tortajada, S., Fuster-Garcia, E., Vicente, J., Wesseling, P., Howe, F. A., Julià-Sapé, M., . . . García-Gómez, J. M. (2011). Incremental gaussian discriminant analysis based on graybill and deal weighted combination of estimators for brain tumour diagnosis. Journal of Biomedical Informatics, 44(4), 677-687. 10.1016/j.jbi.2011.02.009

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/37477

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Title: Incremental gaussian discriminant analysis based on graybill and deal weighted combination of estimators for brain tumour diagnosis
Author:
UPV Unit: Universitat Politècnica de València. Instituto Universitario de Aplicaciones de las Tecnologías de la Información - Institut Universitari d'Aplicacions de les Tecnologies de la Informació
Universitat Politècnica de València. Departamento de Física Aplicada - Departament de Física Aplicada
Issued date:
Abstract:
In the last decade, machine learning (ML) techniques have been used for developing classifiers for automatic brain tumour diagnosis. However, the development of these ML models rely on a unique training set and learning ...[+]
Subjects: Machine learning , Incremental learning , Graybill-Deal estimator , Automatic brain tumour diagnosis , Magnetic resonance , Brain tumours , Empirical results , Gaussians , Incremental algorithm , Number of samples , Preprocess , Training sets , Discriminant analysis , Estimation , Magnetic resonance spectroscopy
Copyrigths: Reserva de todos los derechos
Source:
Journal of Biomedical Informatics. (issn: 1532-0464 )
DOI: 10.1016/j.jbi.2011.02.009
Publisher:
Elsevier
Publisher version: http://dx.doi.org/10.1016/j.jbi.2011.02.009
Thanks:
This work has been partially funded by the Spanish Institut de Salud Carlos III (ISCiii) through the RETICS Combiomed (RD07/0067/2001). The authors thank the Programa Torres Quevedo from Ministerio de Educacion y Ciencia, ...[+]
Type: Artículo

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