BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

117 related articles for article (PubMed ID: 18343526)

  • 1. Improving accuracy in astrocytomas grading by integrating a robust least squares mapping driven support vector machine classifier into a two level grade classification scheme.
    Glotsos D; Kalatzis I; Spyridonos P; Kostopoulos S; Daskalakis A; Athanasiadis E; Ravazoula P; Nikiforidis G; Cavouras D
    Comput Methods Programs Biomed; 2008 Jun; 90(3):251-61. PubMed ID: 18343526
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Brain tumor classification based on long echo proton MRS signals.
    Lukas L; Devos A; Suykens JA; Vanhamme L; Howe FA; Majós C; Moreno-Torres A; Van der Graaf M; Tate AR; Arús C; Van Huffel S
    Artif Intell Med; 2004 May; 31(1):73-89. PubMed ID: 15182848
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Distribution of nuclear size and internuclear distance are important criteria for grading astrocytomas.
    Nafe R; Van de Nes J; Yan B; Schlote W
    Clin Neuropathol; 2006; 25(1):48-56. PubMed ID: 16465775
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Bayesian framework for least-squares support vector machine classifiers, gaussian processes, and kernel Fisher discriminant analysis.
    Van Gestel T; Suykens JA; Lanckriet G; Lambrechts A; De Moor B; Vandewalle J
    Neural Comput; 2002 May; 14(5):1115-47. PubMed ID: 11972910
    [TBL] [Abstract][Full Text] [Related]  

  • 5. An image-analysis system based on support vector machines for automatic grade diagnosis of brain-tumour astrocytomas in clinical routine.
    Glotsos D; Spyridonos P; Cavouras D; Ravazoula P; Dadioti PA; Nikiforidis G
    Med Inform Internet Med; 2005 Sep; 30(3):179-93. PubMed ID: 16403707
    [TBL] [Abstract][Full Text] [Related]  

  • 6. New support vector-based design method for binary hierarchical classifiers for multi-class classification problems.
    Wang YC; Casasent D
    Neural Netw; 2008; 21(2-3):502-10. PubMed ID: 18187285
    [TBL] [Abstract][Full Text] [Related]  

  • 7. The effect of combining two echo times in automatic brain tumor classification by MRS.
    García-Gómez JM; Tortajada S; Vidal C; Julià-Sapé M; Luts J; Moreno-Torres A; Van Huffel S; Arús C; Robles M
    NMR Biomed; 2008 Nov; 21(10):1112-25. PubMed ID: 18759382
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Classification of electrocardiogram signals with support vector machines and particle swarm optimization.
    Melgani F; Bazi Y
    IEEE Trans Inf Technol Biomed; 2008 Sep; 12(5):667-77. PubMed ID: 18779082
    [TBL] [Abstract][Full Text] [Related]  

  • 9. [Computer assisted grading of gliomas of the astrocytoma/glioblastoma groups].
    Kolles H; von Wangenheim A; Niedermayer I; Vince GH; Feiden W
    Verh Dtsch Ges Pathol; 1994; 78():427-31. PubMed ID: 7534014
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Computer-based malignancy grading of astrocytomas employing a support vector machine classifier, the WHO grading system and the regular hematoxylin-eosin diagnostic staining procedure.
    Glotsos D; Spyridonos P; Petalas P; Cavouras D; Ravazoula P; Dadioti PA; Lekka I; Nikiforidis G
    Anal Quant Cytol Histol; 2004 Apr; 26(2):77-83. PubMed ID: 15131894
    [TBL] [Abstract][Full Text] [Related]  

  • 11. The application of mutual information-based feature selection and fuzzy LS-SVM-based classifier in motion classification.
    Yan Z; Wang Z; Xie H
    Comput Methods Programs Biomed; 2008 Jun; 90(3):275-84. PubMed ID: 18295367
    [TBL] [Abstract][Full Text] [Related]  

  • 12. The use of multivariate MR imaging intensities versus metabolic data from MR spectroscopic imaging for brain tumour classification.
    Devos A; Simonetti AW; van der Graaf M; Lukas L; Suykens JA; Vanhamme L; Buydens LM; Heerschap A; Van Huffel S
    J Magn Reson; 2005 Apr; 173(2):218-28. PubMed ID: 15780914
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Between classification-error approximation and weighted least-squares learning.
    Toh KA; Eng HL
    IEEE Trans Pattern Anal Mach Intell; 2008 Apr; 30(4):658-69. PubMed ID: 18276971
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Tackling EEG signal classification with least squares support vector machines: a sensitivity analysis study.
    Lima CA; Coelho AL; Eisencraft M
    Comput Biol Med; 2010 Aug; 40(8):705-14. PubMed ID: 20621291
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Automatic classification of athletes with residual functional deficits following concussion by means of EEG signal using support vector machine.
    Cao C; Tutwiler RL; Slobounov S
    IEEE Trans Neural Syst Rehabil Eng; 2008 Aug; 16(4):327-35. PubMed ID: 18701381
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Handling missing values in support vector machine classifiers.
    Pelckmans K; De Brabanter J; Suykens JA; De Moor B
    Neural Netw; 2005; 18(5-6):684-92. PubMed ID: 16111866
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Automated computer differential classification in Parkinsonian Syndromes via pattern analysis on MRI.
    Duchesne S; Rolland Y; Vérin M
    Acad Radiol; 2009 Jan; 16(1):61-70. PubMed ID: 19064213
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Low rank updated LS-SVM classifiers for fast variable selection.
    Ojeda F; Suykens JA; De Moor B
    Neural Netw; 2008; 21(2-3):437-49. PubMed ID: 18343309
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Support Vectors Machine-based identification of heart valve diseases using heart sounds.
    Maglogiannis I; Loukis E; Zafiropoulos E; Stasis A
    Comput Methods Programs Biomed; 2009 Jul; 95(1):47-61. PubMed ID: 19269056
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Automated diagnosis of brain tumours astrocytomas using probabilistic neural network clustering and support vector machines.
    Glotsos D; Tohka J; Ravazoula P; Cavouras D; Nikiforidis G
    Int J Neural Syst; 2005; 15(1-2):1-11. PubMed ID: 15912578
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.