David Nordsletten

4.3k total citations
121 papers, 2.8k citations indexed

About

David Nordsletten is a scholar working on Cardiology and Cardiovascular Medicine, Biomedical Engineering and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, David Nordsletten has authored 121 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Cardiology and Cardiovascular Medicine, 52 papers in Biomedical Engineering and 39 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in David Nordsletten's work include Cardiovascular Function and Risk Factors (46 papers), Elasticity and Material Modeling (41 papers) and Cardiac Valve Diseases and Treatments (28 papers). David Nordsletten is often cited by papers focused on Cardiovascular Function and Risk Factors (46 papers), Elasticity and Material Modeling (41 papers) and Cardiac Valve Diseases and Treatments (28 papers). David Nordsletten collaborates with scholars based in United Kingdom, United States and New Zealand. David Nordsletten's co-authors include Nicolas P. Smith, Jack Lee, Pablo Lamata, Ralph Sinkus, Steven Niederer, Radomír Chabiniok, David Kay, C. Alberto Figueroa, Myrianthi Hadjicharalambous and Peter Hunter and has published in prestigious journals such as Physical Review Letters, Nature Communications and Journal of the American College of Cardiology.

In The Last Decade

David Nordsletten

118 papers receiving 2.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
David Nordsletten United Kingdom	31	1.5k	1.1k	854	496	420	121	2.8k
Hao Gao United Kingdom	28	1.0k 0.7×	963 0.9×	490 0.6×	475 1.0×	293 0.7×	133	2.0k
Jack Lee United Kingdom	29	950 0.6×	642 0.6×	773 0.9×	416 0.8×	353 0.8×	85	2.2k
D. Rodney Hose United Kingdom	30	1.1k 0.7×	763 0.7×	853 1.0×	1.2k 2.4×	535 1.3×	116	3.0k
Hyun Jin Kim South Korea	23	990 0.7×	400 0.4×	764 0.9×	1.1k 2.2×	493 1.2×	72	2.3k
Johan G. Bosch Netherlands	29	1.2k 0.8×	1.3k 1.3×	1.9k 2.2×	581 1.2×	554 1.3×	231	3.5k
Olivier Bernard France	32	635 0.4×	721 0.7×	1.2k 1.5×	671 1.4×	224 0.5×	123	2.8k
Patricia V. Lawford United Kingdom	29	1.2k 0.8×	542 0.5×	611 0.7×	1.2k 2.5×	680 1.6×	108	2.7k
Jordi Alastruey United Kingdom	33	2.8k 1.9×	1.4k 1.3×	649 0.8×	1.3k 2.7×	747 1.8×	104	3.9k
Christian Vergara Italy	30	1.2k 0.8×	581 0.5×	229 0.3×	583 1.2×	516 1.2×	121	2.8k
Pablo Lamata United Kingdom	30	1.8k 1.2×	790 0.7×	891 1.0×	797 1.6×	463 1.1×	158	3.2k

Countries citing papers authored by David Nordsletten

Since Specialization

Citations

This map shows the geographic impact of David Nordsletten's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by David Nordsletten with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Nordsletten more than expected).

Fields of papers citing papers by David Nordsletten

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Nordsletten. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by David Nordsletten. The network helps show where David Nordsletten may publish in the future.

Co-authorship network of co-authors of David Nordsletten

This figure shows the co-authorship network connecting the top 25 collaborators of David Nordsletten. A scholar is included among the top collaborators of David Nordsletten based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David Nordsletten. David Nordsletten is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Lip, Gregory Y H, et al.. (2025). MRI-based modelling of left atrial flow and coagulation to predict risk of thrombogenesis in atrial fibrillation. Medical Image Analysis. 101. 103475–103475. 5 indexed citations

Holm, Sverre, Rami Mustapha, Katharina Schregel, et al.. (2024). Making sense of scattering: Seeing microstructure through shear waves. Science Advances. 10(31). eadp3363–eadp3363.

Akbar, Muhammad Usman, Jonas Schollenberger, Nicholas S. Burris, et al.. (2024). Generalized Super-Resolution 4D Flow MRI - Using Ensemble Learning to Extend Across the Cardiovascular System. IEEE Journal of Biomedical and Health Informatics. 28(12). 7239–7250. 5 indexed citations

Zhang, Will, et al.. (2023). A viscoelastic constitutive model for human femoropopliteal arteries. Acta Biomaterialia. 170. 68–85. 7 indexed citations

Zhang, Will, et al.. (2023). Simulating hyperelasticity and fractional viscoelasticity in the human heart. Computer Methods in Applied Mechanics and Engineering. 411. 116048–116048. 14 indexed citations

Lip, Gregory Y.H., et al.. (2023). Imaging and biophysical modelling of thrombogenic mechanisms in atrial fibrillation and stroke. Frontiers in Cardiovascular Medicine. 9. 1074562–1074562. 19 indexed citations

Williams, Steven E., et al.. (2023). The impact of aging and atrial fibrillation on thrombus formation in-silico. European Heart Journal. 44(Supplement_2). 2 indexed citations

Nordsletten, David, et al.. (2022). Fluid-reduced-Solid Interaction (FrSI): Physics- and Projection-Based Model Reduction for Cardiovascular Applications. SSRN Electronic Journal. 1 indexed citations

Williams, Steven, et al.. (2022). Modelling Virchow's Triad to Improve Stroke Risk Assessment in Atrial Fibrillation Patients. Computing in cardiology. 49. 2 indexed citations

10.

Nordsletten, David, et al.. (2022). Personalization of biomechanical simulations of the left ventricle by in-vivo cardiac DTI data: Impact of fiber interpolation methods. Frontiers in Physiology. 13. 1042537–1042537. 7 indexed citations

11.

Fernandes, João Filipe, Omar Chehab, Bernard Prendergast, et al.. (2021). Evaluation of aortic stenosis: From Bernoulli and Doppler to Navier-Stokes. Trends in Cardiovascular Medicine. 33(1). 32–43. 8 indexed citations

12.

Zhao, Yan-Ting, Yu‐Wei Wu, Daniel L. Matera, et al.. (2021). Physiologic biomechanics enhance reproducible contractile development in a stem cell derived cardiac muscle platform. Nature Communications. 12(1). 6167–6167. 30 indexed citations

13.

Bilston, Lynne E., et al.. (2020). Nonlinear viscoelastic constitutive model for bovine liver tissue. Biomechanics and Modeling in Mechanobiology. 19(5). 1641–1662. 29 indexed citations

14.

Nama, Nitesh, Frans L. Moll, Joost A. van Herwaarden, et al.. (2020). Mapping pre-dissection aortic wall abnormalities: a multiparametric assessment. European Journal of Cardio-Thoracic Surgery. 57(6). 1061–1067. 8 indexed citations

15.

Zhang, Will, et al.. (2020). An efficient and accurate method for modeling nonlinear fractional viscoelastic biomaterials. Computer Methods in Applied Mechanics and Engineering. 362. 112834–112834. 40 indexed citations

16.

Burris, Nicholas S., David Nordsletten, Julio Sotelo, et al.. (2019). False lumen ejection fraction predicts growth in type B aortic dissection: preliminary results. European Journal of Cardio-Thoracic Surgery. 57(5). 896–903. 40 indexed citations

17.

Patz, Samuel, Katharina Schregel, Miklós Palotai, et al.. (2019). Imaging localized neuronal activity at fast time scales through biomechanics. Science Advances. 5(4). eaav3816–eaav3816. 34 indexed citations

18.

Runge, Jurgen H., Jack Lee, Marian Troelstra, et al.. (2018). A novel magnetic resonance elastography transducer concept based on a rotational eccentric mass: preliminary experiences with the gravitational transducer. Physics in Medicine and Biology. 64(4). 45007–45007. 34 indexed citations

19.

Vigueras, Guillermo, Ishani Roy, Andrew Cookson, et al.. (2013). Toward GPGPU accelerated human electromechanical cardiac simulations. International Journal for Numerical Methods in Biomedical Engineering. 30(1). 117–134. 16 indexed citations

20.

Lee, Jack, Steven Niederer, David Nordsletten, et al.. (2009). Coupling contraction, excitation, ventricular and coronary blood flow across scale and physics in the heart. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 367(1901). 3331–3331. 7 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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