BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

127 related articles for article (PubMed ID: 38076515)

  • 1. Personalized Predictions of Glioblastoma Infiltration: Mathematical Models, Physics-Informed Neural Networks and Multimodal Scans.
    Zhang RZ; Ezhov I; Balcerak M; Zhu A; Wiestler B; Menze B; Lowengrub J
    ArXiv; 2024 Jan; ():. PubMed ID: 38076515
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans, and Bayesian Inference.
    Lipkova J; Angelikopoulos P; Wu S; Alberts E; Wiestler B; Diehl C; Preibisch C; Pyka T; Combs SE; Hadjidoukas P; Van Leemput K; Koumoutsakos P; Lowengrub J; Menze B
    IEEE Trans Med Imaging; 2019 Aug; 38(8):1875-1884. PubMed ID: 30835219
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Physics-informed neural networks (PINNs) for 4D hemodynamics prediction: An investigation of optimal framework based on vascular morphology.
    Zhang X; Mao B; Che Y; Kang J; Luo M; Qiao A; Liu Y; Anzai H; Ohta M; Guo Y; Li G
    Comput Biol Med; 2023 Sep; 164():107287. PubMed ID: 37536096
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Gradient Statistics-Based Multi-Objective Optimization in Physics-Informed Neural Networks.
    Vemuri SK; Denzler J
    Sensors (Basel); 2023 Oct; 23(21):. PubMed ID: 37960365
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Strategies for multi-case physics-informed neural networks for tube flows: a study using 2D flow scenarios.
    Wong HS; Chan WX; Li BH; Yap CH
    Sci Rep; 2024 May; 14(1):11577. PubMed ID: 38773243
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Physics-Informed Neural Networks Integrating Compartmental Model for Analyzing COVID-19 Transmission Dynamics.
    Ning X; Guan J; Li XA; Wei Y; Chen F
    Viruses; 2023 Aug; 15(8):. PubMed ID: 37632091
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Error estimates and physics informed augmentation of neural networks for thermally coupled incompressible Navier Stokes equations.
    Goraya S; Sobh N; Masud A
    Comput Mech; 2023 Aug; 72(2):267-289. PubMed ID: 37583614
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A Combination of Deep Neural Networks and Physics to Solve the Inverse Problem of Burger's Equation.
    Alkhadhr S; Almekkawy M
    Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():4465-4468. PubMed ID: 34892210
    [TBL] [Abstract][Full Text] [Related]  

  • 9. EP-PINNs: Cardiac Electrophysiology Characterisation Using Physics-Informed Neural Networks.
    Herrero Martin C; Oved A; Chowdhury RA; Ullmann E; Peters NS; Bharath AA; Varela M
    Front Cardiovasc Med; 2021; 8():768419. PubMed ID: 35187101
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Physics-informed kernel function neural networks for solving partial differential equations.
    Fu Z; Xu W; Liu S
    Neural Netw; 2024 Apr; 172():106098. PubMed ID: 38199153
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Physics-informed neural network with transfer learning (TL-PINN) based on domain similarity measure for prediction of nuclear reactor transients.
    Prantikos K; Chatzidakis S; Tsoukalas LH; Heifetz A
    Sci Rep; 2023 Oct; 13(1):16840. PubMed ID: 37803015
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Recipes for when physics fails: recovering robust learning of physics informed neural networks.
    Bajaj C; McLennan L; Andeen T; Roy A
    Mach Learn Sci Technol; 2023 Mar; 4(1):015013. PubMed ID: 37680302
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep learning characterization of brain tumours with diffusion weighted imaging.
    Meaney C; Das S; Colak E; Kohandel M
    J Theor Biol; 2023 Jan; 557():111342. PubMed ID: 36368560
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Physics Informed Neural Networks (PINN) for Low Snr Magnetic Resonance Electrical Properties Tomography (MREPT).
    Inda AJG; Huang SY; İmamoğlu N; Qin R; Yang T; Chen T; Yuan Z; Yu W
    Diagnostics (Basel); 2022 Oct; 12(11):. PubMed ID: 36359471
    [TBL] [Abstract][Full Text] [Related]  

  • 15. On acoustic fields of complex scatters based on physics-informed neural networks.
    Wang H; Li J; Wang L; Liang L; Zeng Z; Liu Y
    Ultrasonics; 2023 Feb; 128():106872. PubMed ID: 36323059
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Non-invasive Inference of Thrombus Material Properties with Physics-Informed Neural Networks.
    Yin M; Zheng X; Humphrey JD; Em Karniadakis G
    Comput Methods Appl Mech Eng; 2021 Mar; 375():. PubMed ID: 33414569
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Self-Scalable Tanh (Stan): Multi-Scale Solutions for Physics-Informed Neural Networks.
    Gnanasambandam R; Shen B; Chung J; Yue X; Kong Z
    IEEE Trans Pattern Anal Mach Intell; 2023 Dec; 45(12):15588-15603. PubMed ID: 37610913
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Constructing Physics-Informed Neural Networks with Architecture Based on Analytical Modification of Numerical Methods by Solving the Problem of Modelling Processes in a Chemical Reactor.
    Tarkhov D; Lazovskaya T; Malykhina G
    Sensors (Basel); 2023 Jan; 23(2):. PubMed ID: 36679461
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Improving microstructural integrity, interstitial fluid, and blood microcirculation images from multi-b-value diffusion MRI using physics-informed neural networks in cerebrovascular disease.
    Voorter PHM; Backes WH; Gurney-Champion OJ; Wong SM; Staals J; van Oostenbrugge RJ; van der Thiel MM; Jansen JFA; Drenthen GS
    Magn Reson Med; 2023 Oct; 90(4):1657-1671. PubMed ID: 37317641
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Parameter Inference for an Astrocyte Model using Machine Learning Approaches.
    Fritschi L; Lenk K
    bioRxiv; 2023 May; ():. PubMed ID: 37292854
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.