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Items: 19

1.

Label noise in subtype discrimination of class C G protein-coupled receptors: A systematic approach to the analysis of classification errors.

König C, Cárdenas MI, Giraldo J, Alquézar R, Vellido A.

BMC Bioinformatics. 2015 Sep 29;16:314. doi: 10.1186/s12859-015-0731-9.

2.
3.

Reducing the n-gram feature space of class C GPCRs to subtype-discriminating patterns.

König C, Alquézar R, Vellido A, Giraldo J.

J Integr Bioinform. 2014 Oct 23;11(3):254. doi: 10.2390/biecoll-jib-2014-254.

PMID:
25339088
4.

Sepsis mortality prediction with the Quotient Basis Kernel.

Ribas Ripoll VJ, Vellido A, Romero E, Ruiz-Rodríguez JC.

Artif Intell Med. 2014 May;61(1):45-52. doi: 10.1016/j.artmed.2014.03.004.

PMID:
24726036
5.

A novel semi-supervised methodology for extracting tumor type-specific MRS sources in human brain data.

Ortega-Martorell S, Ruiz H, Vellido A, Olier I, Romero E, Julià-Sapé M, Martín JD, Jarman IH, Arús C, Lisboa PJ.

PLoS One. 2013 Dec 23;8(12):e83773. doi: 10.1371/journal.pone.0083773.

6.

Convex non-negative matrix factorization for brain tumor delimitation from MRSI data.

Ortega-Martorell S, Lisboa PJ, Vellido A, Simões RV, Pumarola M, Julià-Sapé M, Arús C.

PLoS One. 2012;7(10):e47824. doi: 10.1371/journal.pone.0047824.

7.

Non-negative matrix factorisation methods for the spectral decomposition of MRS data from human brain tumours.

Ortega-Martorell S, Lisboa PJ, Vellido A, Julià-Sapé M, Arús C.

BMC Bioinformatics. 2012 Mar 8;13:38. doi: 10.1186/1471-2105-13-38.

8.

Brain tumour classification using Gaussian decomposition and neural networks.

Arizmendi C, Sierra DA, Vellido A, Romero E.

Conf Proc IEEE Eng Med Biol Soc. 2011;2011:5645-8. doi: 10.1109/IEMBS.2011.6091366.

PMID:
22255620
9.

Severe sepsis mortality prediction with relevance vector machines.

Ribas VJ, López JC, Ruiz-Sanmartin A, Ruiz-Rodríguez JC, Rello J, Wojdel A, Vellido A.

Conf Proc IEEE Eng Med Biol Soc. 2011;2011:100-3. doi: 10.1109/IEMBS.2011.6089906.

PMID:
22254260
10.

Robust discrimination of glioblastomas from metastatic brain tumors on the basis of single-voxel (1)H MRS.

Vellido A, Romero E, Julià-Sapé M, Majós C, Moreno-Torres Á, Pujol J, Arús C.

NMR Biomed. 2012 Jun;25(6):819-28. doi: 10.1002/nbm.1797.

PMID:
22081447
11.
12.

Diagnosis of brain tumours from magnetic resonance spectroscopy using wavelets and Neural Networks.

Arizmendi C, Hernandez-Tamames J, Romero E, Vellido A, Del Pozo F.

Conf Proc IEEE Eng Med Biol Soc. 2010;2010:6074-7. doi: 10.1109/IEMBS.2010.5627627.

PMID:
21097127
13.

Finding discriminative subtypes of aggressive brain tumours using magnetic resonance spectroscopy.

Colas F, Kok JN, Vellido A.

Conf Proc IEEE Eng Med Biol Soc. 2010;2010:1065-8. doi: 10.1109/IEMBS.2010.5627286.

PMID:
21096552
14.

Advances in clustering and visualization of time series using GTM through time.

Olier I, Vellido A.

Neural Netw. 2008 Sep;21(7):904-13. doi: 10.1016/j.neunet.2008.05.013.

PMID:
18653311
15.

Selective smoothing of the generative topographic mapping.

Vellido A, El-Deredy W, Lisboa PG.

IEEE Trans Neural Netw. 2003;14(4):847-52. doi: 10.1109/TNN.2003.813834.

PMID:
18238064
16.

Missing data imputation through GTM as a mixture of t-distributions.

Vellido A.

Neural Netw. 2006 Dec;19(10):1624-35.

PMID:
16580176
17.

Handling outliers in brain tumour MRS data analysis through robust topographic mapping.

Vellido A, Lisboa PJ.

Comput Biol Med. 2006 Oct;36(10):1049-63.

PMID:
16305794
18.

Bias reduction in skewed binary classification with Bayesian neural networks.

Lisboa PJ, Vellido A, Wong H.

Neural Netw. 2000 May-Jun;13(4-5):407-10.

PMID:
10946389
19.

Assessment of statistical and neural networks methods in NMR spectral classification and metabolite selection.

Lisboa PJ, Kirby SP, Vellido A, Lee YY, El-Deredy W.

NMR Biomed. 1998 Jun-Aug;11(4-5):225-34.

PMID:
9719577
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