Revistas 2011

Herramientas para elaborar métodos de CAD del cáncer de mama.Una colaboración entre el CIEMAT y las Facultades de Ingeniería y Medicina de la Universidad de Porto

Autor

Guillermo Díaz Herrero, Jose Miguel Franco Valiente, César Suárez Ortega, Manuel Rubio del Solar, Raúl Ramos Pollán, Miguel Ángel Guevara López, Naimy González de Posada, Isabel Ramos y Joana Loureiro

Medio de publicación

Revista Vértices
Fecha: 1 de Diciembre, 2011
Tipo de publicación: Revista

Discovering Mammography-based Machine Learning Classifiers for Breast Cancer Diagnosis

Autor

Raúl Ramos-Pollán, Miguel Angel Guevara-López, Cesar Suárez-Ortega, Guillermo Díaz-Herrero, Jose Miguel Franco-Valiente, Manuel Rubio-del-Solar, Naimy González-de-Posada, Mario Augusto Pires Vaz, Joana Loureiro and Isabel Ramos

Journal of Medical Systems: 1-11. 2011

(http://dx.doi.org/10.1007/s10916-011-9693-2)

A Software Framework for Building Biomedical Machine Learning Classifiers through Grid Computing Resources

Autor

Raúl Ramos-Pollán, Miguel Angel Guevara López, Eugénio Oliveira

Journal of Medical Systems: 1-13. 2011

(http://dx.doi.org/10.1007/s10916-011-9692-3)

Abstract

This paper describes the BiomedTK software framework, created to perform massive explorations of machine learning classifiers configurations for biomedical data analysis over distributed Grid computing resources. BiomedTK integrates ROC analysis throughout the complete classifier construction process and enables explorations of large parameter sweeps for training third party classifiers such as artificial neural networks and support vector machines, offering the capability to harness the vast amount of computing power serviced by Grid infrastructures.

In addition, it includes classifiers modified by the authors for ROC optimization and functionality to build ensemble classifiers and manipulate datasets (import/export, extract and transform data, etc.). BiomedTK was experimentally validated by training thousands of classifier configurations for representative biomedical UCI datasets reaching in little time classification levels comparable to those reported in existing literature. The comprehensive method herewith presented represents an improvement to biomedical data analysis in both methodology and potential reach of machine learning based experimentation.

Application Workflow Deployments on Computing Grids with a Complex Network Topology

Autor

Francisco Prieto-Castrillo, Antonio Astillero, Elena Rey-Espada, María Botón-Fernández, María Arsuaga-Ríos

Publicación JCR
International Journal of Complex Systems in Science, Volume 1, Issue 2, Interlude, 2011
pp. 89-95, ISSN: 2174-6036