These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

193 related articles for article (PubMed ID: 33109017)

  • 1. Sensitivity analysis of an electrophysiology model for the left ventricle.
    Del Corso G; Verzicco R; Viola F
    J R Soc Interface; 2020 Oct; 17(171):20200532. PubMed ID: 33109017
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Uncertainty in cardiac myofiber orientation and stiffnesses dominate the variability of left ventricle deformation response.
    Rodríguez-Cantano R; Sundnes J; Rognes ME
    Int J Numer Method Biomed Eng; 2019 May; 35(5):e3178. PubMed ID: 30632711
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Generalized polynomial chaos-based uncertainty quantification and propagation in multi-scale modeling of cardiac electrophysiology.
    Hu Z; Du D; Du Y
    Comput Biol Med; 2018 Nov; 102():57-74. PubMed ID: 30248513
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Efficient sampling for polynomial chaos-based uncertainty quantification and sensitivity analysis using weighted approximate Fekete points.
    Burk KM; Narayan A; Orr JA
    Int J Numer Method Biomed Eng; 2020 Nov; 36(11):e3395. PubMed ID: 32794272
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Sensitivity analysis and inverse uncertainty quantification for the left ventricular passive mechanics.
    Lazarus A; Dalton D; Husmeier D; Gao H
    Biomech Model Mechanobiol; 2022 Jun; 21(3):953-982. PubMed ID: 35377030
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Quantifying the uncertainty in model parameters using Gaussian process-based Markov chain Monte Carlo in cardiac electrophysiology.
    Dhamala J; Arevalo HJ; Sapp J; Horácek BM; Wu KC; Trayanova NA; Wang L
    Med Image Anal; 2018 Aug; 48():43-57. PubMed ID: 29843078
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A guide to uncertainty quantification and sensitivity analysis for cardiovascular applications.
    Eck VG; Donders WP; Sturdy J; Feinberg J; Delhaas T; Hellevik LR; Huberts W
    Int J Numer Method Biomed Eng; 2016 Aug; 32(8):. PubMed ID: 26475178
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Personalization of models with many model parameters: an efficient sensitivity analysis approach.
    Donders WP; Huberts W; van de Vosse FN; Delhaas T
    Int J Numer Method Biomed Eng; 2015 Oct; 31(10):. PubMed ID: 26017545
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Using UncertainSCI to Quantify Uncertainty in Cardiac Simulations.
    Rupp LC; Liu Z; Bergquist JA; Rampersad S; White D; Tate JD; Brooks DH; Narayan A; MacLeod RS
    Comput Cardiol (2010); 2020 Sep; 47():. PubMed ID: 36845870
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A Metamodeling Approach for Instant Severity Assessment and Uncertainty Quantification of Iliac Artery Stenoses.
    Heinen SGH; Gashi K; van den Heuvel DAF; de Vries JPPM; van de Vosse FN; Delhaas T; Huberts W
    J Biomech Eng; 2020 Jan; 142(1):. PubMed ID: 31513713
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Global sensitivity analysis with multifidelity Monte Carlo and polynomial chaos expansion for vascular haemodynamics.
    Schäfer F; Schiavazzi DE; Hellevik LR; Sturdy J
    Int J Numer Method Biomed Eng; 2024 Jun; ():e3836. PubMed ID: 38837871
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Comprehensive Uncertainty Quantification and Sensitivity Analysis for Cardiac Action Potential Models.
    Pathmanathan P; Cordeiro JM; Gray RA
    Front Physiol; 2019; 10():721. PubMed ID: 31297060
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Effects of left ventricle wall thickness uncertainties on cardiac mechanics.
    Campos JO; Sundnes J; Dos Santos RW; Rocha BM
    Biomech Model Mechanobiol; 2019 Oct; 18(5):1415-1427. PubMed ID: 31025130
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Uncertainty quantification for ecological models with random parameters.
    Reimer JR; Adler FR; Golden KM; Narayan A
    Ecol Lett; 2022 Oct; 25(10):2232-2244. PubMed ID: 36068942
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Fast uncertainty quantification for dynamic flux balance analysis using non-smooth polynomial chaos expansions.
    Paulson JA; Martin-Casas M; Mesbah A
    PLoS Comput Biol; 2019 Aug; 15(8):e1007308. PubMed ID: 31469832
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Propagation of Parametric Uncertainty in Aliev-Panfilov Model of Cardiac Excitation.
    Son J; Du Y; Du D
    Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():5450-5453. PubMed ID: 30441570
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Enabling forward uncertainty quantification and sensitivity analysis in cardiac electrophysiology by reduced order modeling and machine learning.
    Pagani S; Manzoni A
    Int J Numer Method Biomed Eng; 2021 Jun; 37(6):e3450. PubMed ID: 33599106
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Uncertainty quantification of the effect of cardiac position variability in the inverse problem of electrocardiographic imaging.
    Bergquist JA; Zenger B; Rupp LC; Busatto A; Tate J; Brooks DH; Narayan A; MacLeod RS
    Physiol Meas; 2023 Oct; 44(10):. PubMed ID: 37734339
    [No Abstract]   [Full Text] [Related]  

  • 19. Fast uncertainty quantification of tracer distribution in the brain interstitial fluid with multilevel and quasi Monte Carlo.
    Croci M; Vinje V; Rognes ME
    Int J Numer Method Biomed Eng; 2021 Jan; 37(1):e3412. PubMed ID: 33174347
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Statistical Framework for Uncertainty Quantification in Computational Molecular Modeling.
    Rasheed M; Clement N; Bhowmick A; Bajaj CL
    IEEE/ACM Trans Comput Biol Bioinform; 2019; 16(4):1154-1167. PubMed ID: 29989988
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.