TY - GEN
T1 - Classification, dimensionality reduction, and maximally discriminatory visualization of a multicentre H-MRS database of brain tumors
AU - Lisboa, Paulo J.G.
AU - Romero, Enrique
AU - Vellido, Alfredo
AU - Julià-Sapé, Margarida
AU - Arüs, Carles
PY - 2008
Y1 - 2008
N2 - The combination of an Artificial Neural Network classifier, a feature selection process, and a novel linear dimensionality reduction technique that provides a data projection for visualization and which preserves completely the class discrimination achieved by the classifier, is applied in this study to the analysis of an international, multi-centre 1H-MRS database of brain tumors. This combination yields results that are both intuitively interpretable and. very accurate. The method as a whole remains simple enough as to allow its easy integration in existing medical decision support systems.
AB - The combination of an Artificial Neural Network classifier, a feature selection process, and a novel linear dimensionality reduction technique that provides a data projection for visualization and which preserves completely the class discrimination achieved by the classifier, is applied in this study to the analysis of an international, multi-centre 1H-MRS database of brain tumors. This combination yields results that are both intuitively interpretable and. very accurate. The method as a whole remains simple enough as to allow its easy integration in existing medical decision support systems.
UR - http://www.scopus.com/inward/record.url?scp=60649096874&partnerID=8YFLogxK
U2 - 10.1109/ICMLA.2008.20
DO - 10.1109/ICMLA.2008.20
M3 - Other contribution
AN - SCOPUS:60649096874
SN - 9780769534954
T3 - Proceedings - 7th International Conference on Machine Learning and Applications, ICMLA 2008
ER -