BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

119 related articles for article (PubMed ID: 10566358)

  • 1. Evaluating variable selection methods for diagnosis of myocardial infarction.
    Dreiseitl S; Ohno-Machado L; Vinterbo S
    Proc AMIA Symp; 1999; ():246-50. PubMed ID: 10566358
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A genetic algorithm to select variables in logistic regression: example in the domain of myocardial infarction.
    Vinterbo S; Ohno-Machado L
    Proc AMIA Symp; 1999; ():984-8. PubMed ID: 10566508
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Using classification tree and logistic regression methods to diagnose myocardial infarction.
    Tsien CL; Fraser HS; Long WJ; Kennedy RL
    Stud Health Technol Inform; 1998; 52 Pt 1():493-7. PubMed ID: 10384505
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Automated variable selection methods for logistic regression produced unstable models for predicting acute myocardial infarction mortality.
    Austin PC; Tu JV
    J Clin Epidemiol; 2004 Nov; 57(11):1138-46. PubMed ID: 15567629
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Selection of predictor variables for pneumonia using neural networks and genetic algorithms.
    Heckerling PS; Gerber BS; Tape TG; Wigton RS
    Methods Inf Med; 2005; 44(1):89-97. PubMed ID: 15778799
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Avoiding overfitting in multilayer perceptrons with feeling-of-knowing using self-organizing maps.
    Murakoshi K
    Biosystems; 2005 Apr; 80(1):37-40. PubMed ID: 15740833
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Artificial neural network algorithms for early diagnosis of acute myocardial infarction and prediction of infarct size in chest pain patients.
    Eggers KM; Ellenius J; Dellborg M; Groth T; Oldgren J; Swahn E; Lindahl B
    Int J Cardiol; 2007 Jan; 114(3):366-74. PubMed ID: 16797088
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Mining for diagnostic information in body surface potential maps: a comparison of feature selection techniques.
    Finlay DD; Nugent CD; McCullagh PJ; Black ND
    Biomed Eng Online; 2005 Sep; 4():51. PubMed ID: 16138921
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Diagnostic ECG classification based on neural networks.
    Bortolan G; Willems JL
    J Electrocardiol; 1993; 26 Suppl():75-9. PubMed ID: 8189152
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Myocardial infarction prediction by artificial neural networks.
    Zelicoff AP
    Ann Intern Med; 1992 Apr; 116(8):701; author reply 702. PubMed ID: 1546880
    [No Abstract]   [Full Text] [Related]  

  • 11. Logistic regression by means of evolutionary radial basis function neural networks.
    Gutierrez PA; Hervas-Martinez C; Martinez-Estudillo FJ
    IEEE Trans Neural Netw; 2011 Feb; 22(2):246-63. PubMed ID: 21138802
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Neural network learning without backpropagation.
    Wilamowski BM; Yu H
    IEEE Trans Neural Netw; 2010 Nov; 21(11):1793-803. PubMed ID: 20858577
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comparison of recent methods for inference of variable influence in neural networks.
    Papadokonstantakis S; Lygeros A; Jacobsson SP
    Neural Netw; 2006 May; 19(4):500-13. PubMed ID: 16352417
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Application of irregular and unbalanced data to predict diabetic nephropathy using visualization and feature selection methods.
    Cho BH; Yu H; Kim KW; Kim TH; Kim IY; Kim SI
    Artif Intell Med; 2008 Jan; 42(1):37-53. PubMed ID: 17997291
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Improving machine learning performance by removing redundant cases in medical data sets.
    Ohno-Machado L; Fraser HS; Ohrn A
    Proc AMIA Symp; 1998; ():523-7. PubMed ID: 9929274
    [TBL] [Abstract][Full Text] [Related]  

  • 16. An evaluation of Bayesian techniques for controlling model complexity and selecting inputs in a neural network for short-term load forecasting.
    Hippert HS; Taylor JW
    Neural Netw; 2010 Apr; 23(3):386-95. PubMed ID: 20022462
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Performance of using multiple stepwise algorithms for variable selection.
    Wiegand RE
    Stat Med; 2010 Jul; 29(15):1647-59. PubMed ID: 20552568
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Machine learning approaches for estimation of prediction interval for the model output.
    Shrestha DL; Solomatine DP
    Neural Netw; 2006 Mar; 19(2):225-35. PubMed ID: 16530384
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Neural architecture design based on extreme learning machine.
    Bueno-Crespo A; García-Laencina PJ; Sancho-Gómez JL
    Neural Netw; 2013 Dec; 48():19-24. PubMed ID: 23892908
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Self-organizing multilayer perceptron.
    Gas B
    IEEE Trans Neural Netw; 2010 Nov; 21(11):1766-79. PubMed ID: 20858579
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.