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Browsing by Author "Arús, Carles"

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Browsing by Author "Arús, Carles"

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    Automated Brain Tumor biopsy prediction using single-labeling cDNA Microarrays-based gene expression profiling 
    Castells, Xavier; Garcia-Gomez, Juan M; Navarro, Alfredo; Acebes, Juan José; Godino, Óscar; Boluda, Susana; Barceló, Anna; Robles, Montserrat; Ariño, Joaquín; Arús, Carles (Lippincott Williams & Wilkins, 2009-12)
    [EN] Aims: Gene signatures obtained from microarray experiments may be of use to improve the prediction of brain tumor diagnosis. Nevertheless, automated and objective prediction with accuracy comparable to or better than ...
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    Compatibility between 3T 1H SV-MRS data and automatic brain tumour diagnosis support systems based on databases of 1.5T 1H SV-MRS spectra 
    Fuster García, Elíes; Navarro., Clara; Vicente Robledo, Javier; Tortajada Velert, Salvador; García Gómez, Juan Miguel; Sáez Silvestre, Carlos; Calvar ., Jorge; Griffiths ., John; Julia Sape, Margarita; Howe ., Franklyn A; Pujol ., Jesús; Peet ., Andrew C; Heerschap ., Arend; Moreno Torres, Àngel; Martínez-Bisbal, M.Carmen; Martinez Granados, Beatriz; Wesseling ., Pieter; Semmler ., Wolfhard; Capellades ., Jaume; Majós ., Carles; Alberich Bayarri, Ángel; Capdevila ., Antoni; Monleón ., Daniel; Marti Bonmati, Luis; Arús ., Carles; Celda ., Bernardo; Robles Viejo, Montserrat (Springer Verlag (Germany), 2011-02)
    Object: This study demonstrates that 3T SV-MRS data can be used with the currently available automatic brain tumour diagnostic classifiers which were trained on databases of 1.5T spectra. This will allow the existing large ...
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    HealthAgents: distributed multi-agent brain tumor diagnosis and prognosis 
    González-Vélez, Horacio; Mier, Mariola; Julià-Sapé, Margarida; Arvanitis, Theodoros N.; García Gómez, Juan Miguel; Robles Viejo, Monserrat; Lewis, Paul H.; Dasmahapatra, Srinandan; Dupplaw, David; Peet, Andrew Charles; Arús, Carles; Celda Muñoz, Bernardo; Van Huffel, Sabine; Lluch-Ariet, Magí (2009)
    [EN] We present an agent-based distributed decision support system for the diagnosis and prognosis of brain tumors developed by the HealthAgents project. HealthAgents is a European Union funded research project, which aims ...
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    Incremental gaussian discriminant analysis based on graybill and deal weighted combination of estimators for brain tumour diagnosis 
    Tortajada Velert, Salvador; Fuster García, Elíes; Vicente Robledo, Javier; Wesseling, Pieter; Howe, Franklyn; Julià-Sapé, Margarida; Candiota, Ana-Paula; Monleón, Daniel; Moreno-Torres, Àngel; Pujol, Jesús; Griffiths, Jonh R.; Wright, Alan; Peet, Andrew C.; Martínez-Bisbal, M. Carmen; Celda, Bernardo; Arús, Carles; Robles Viejo, Montserrat; García Gómez, Juan Miguel (Elsevier, 2011-08)
    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 ...
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    Multiproject-multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy 
    Garcia-Gomez, Juan M; Luts, Jan; Julia-Sape, Margarida; Krooshof, Patrick; Tortajada Velert, Salvador; Vicente Robledo, Javier; Melssen, Willem; Fuster García, Elíes; Olier, Ivan; Postma, Geert; Monleon, Daniel; Moreno-Torres, Angel; Pujol, Jesus; Candiota, Ana-Paula; Martínez-Bisbal, M.Carmen; Suykens, Johan; Buydens, Lutgarde; Celda, Bernardo; Van Huffel, Sabine; Arus, Carles; Robles Viejo, Montserrat (Springer-Verlag, 2009-02)
    [EN] Automatic brain tumor classification by MRS has been under development for more than a decade. Nonetheless, to our knowledge, there are no published evaluations of predictive models with unseen cases that are subsequently ...
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    The effect of combining two echo times in automatic brain tumor classification by MRS 
    García-Gómez, Juan M; Tortajada, Salvador; Vidal, César; Julià -Sapé, Margalida; Luts, Jan; Moreno-Torres, Àngel; Van Huffel, Sabine; Arús, Carles; Robles Viejo, Montserrat (John Wiley & Sons, 2008-12)
    [EN] H-1 MRS is becoming an accurate, non-invasive technique for initial examination of brain masses. We investigated if the combination of single-voxel H-1 MRS at 1.5 T at two different (TEs), short TE (PRESS or STEAM, ...