| Outbreak dynamics of COVID-19 in Europe and the effect of travel restrictions K Linka, M Peirlinck, F Sahli Costabal, E Kuhl Computer methods in biomechanics and biomedical engineering 23 (11), 710-717, 2020 | 404 | 2020 |
| Physics-informed neural networks for cardiac activation mapping F Sahli Costabal, Y Yang, P Perdikaris, DE Hurtado, E Kuhl Frontiers in Physics 8, 42, 2020 | 394 | 2020 |
| Outbreak dynamics of COVID-19 in China and the United States M Peirlinck, K Linka, F Sahli Costabal, E Kuhl Biomechanics and modeling in mechanobiology 19 (6), 2179-2193, 2020 | 198 | 2020 |
| Precision medicine in human heart modeling: perspectives, challenges, and opportunities M Peirlinck, FS Costabal, J Yao, JM Guccione, S Tripathy, Y Wang, ... Biomechanics and modeling in mechanobiology 20, 803-831, 2021 | 187 | 2021 |
| Generating Purkinje networks in the human heart FS Costabal, DE Hurtado, E Kuhl Journal of biomechanics 49 (12), 2455-2465, 2016 | 135 | 2016 |
| Machine learning in drug development: Characterizing the effect of 30 drugs on the QT interval using Gaussian process regression, sensitivity analysis, and uncertainty … FS Costabal, K Matsuno, J Yao, P Perdikaris, E Kuhl Computer Methods in Applied Mechanics and Engineering 348, 313-333, 2019 | 101 | 2019 |
| Visualizing the invisible: The effect of asymptomatic transmission on the outbreak dynamics of COVID-19 M Peirlinck, K Linka, FS Costabal, J Bhattacharya, E Bendavid, ... Computer Methods in Applied Mechanics and Engineering 372, 113410, 2020 | 98 | 2020 |
| Using machine learning to characterize heart failure across the scales M Peirlinck, F Sahli Costabal, KL Sack, JS Choy, GS Kassab, ... Biomechanics and modeling in mechanobiology 18 (6), 1987-2001, 2019 | 74 | 2019 |
| The importance of mechano-electrical feedback and inertia in cardiac electromechanics FS Costabal, FA Concha, DE Hurtado, E Kuhl Computer methods in applied mechanics and engineering 320, 352-368, 2017 | 74 | 2017 |
| Data-driven tissue mechanics with polyconvex neural ordinary differential equations V Tac, FS Costabal, AB Tepole Computer Methods in Applied Mechanics and Engineering 398, 115248, 2022 | 71 | 2022 |
| COVID-19 dynamics across the US: A deep learning study of human mobility and social behavior MA Bhouri, FS Costabal, H Wang, K Linka, M Peirlinck, E Kuhl, ... Computer Methods in Applied Mechanics and Engineering 382, 113891, 2021 | 69 | 2021 |
| Multi-fidelity classification using Gaussian processes: accelerating the prediction of large-scale computational models FS Costabal, P Perdikaris, E Kuhl, DE Hurtado Computer Methods in Applied Mechanics and Engineering 357, 112602, 2019 | 63 | 2019 |
| Benchmarking physics-informed frameworks for data-driven hyperelasticity V Taç, K Linka, F Sahli-Costabal, E Kuhl, AB Tepole Computational mechanics 73 (1), 49-65, 2024 | 49* | 2024 |
| Predicting drug‐induced arrhythmias by multiscale modeling F Sahli Costabal, J Yao, E Kuhl International journal for numerical methods in biomedical engineering 34 (5 …, 2018 | 48 | 2018 |
| Multiscale characterization of heart failure FS Costabal, JS Choy, KL Sack, JM Guccione, GS Kassab, E Kuhl Acta biomaterialia 86, 66-76, 2019 | 45 | 2019 |
| Seeing double: a comparison of microstructure, biomechanical function, and adjacent disc health between double-and single-layer vertebral endplates AJ Fields, F Sahli, AG Rodriguez, JC Lotz Spine 37 (21), E1310-E1317, 2012 | 44 | 2012 |
| Physics-informed neural networks to learn cardiac fiber orientation from multiple electroanatomical maps C Ruiz Herrera, T Grandits, G Plank, P Perdikaris, F Sahli Costabal, ... Engineering with Computers 38 (5), 3957-3973, 2022 | 40 | 2022 |
| Data-driven anisotropic finite viscoelasticity using neural ordinary differential equations V Taç, MK Rausch, FS Costabal, AB Tepole Computer methods in applied mechanics and engineering 411, 116046, 2023 | 36 | 2023 |
| Δ-PINNs: physics-informed neural networks on complex geometries FS Costabal, S Pezzuto, P Perdikaris Engineering Applications of Artificial Intelligence 127, 107324, 2024 | 32 | 2024 |
| Classifying drugs by their arrhythmogenic risk using machine learning F Sahli-Costabal, K Seo, E Ashley, E Kuhl Biophysical journal 118 (5), 1165-1176, 2020 | 32 | 2020 |
Ellen KuhlCatherine Holman Johnson Director of Stanford Bio-X and Walter B. Reinhold Professor of EngineeringΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα stanford.edu