Pavlo Yevtushenko

460 total citations
17 papers, 304 citations indexed

About

Pavlo Yevtushenko is a scholar working on Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine and Epidemiology. According to data from OpenAlex, Pavlo Yevtushenko has authored 17 papers receiving a total of 304 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Cardiology and Cardiovascular Medicine, 8 papers in Pulmonary and Respiratory Medicine and 8 papers in Epidemiology. Recurrent topics in Pavlo Yevtushenko's work include Cardiac Valve Diseases and Treatments (12 papers), Cardiovascular Function and Risk Factors (12 papers) and Congenital Heart Disease Studies (8 papers). Pavlo Yevtushenko is often cited by papers focused on Cardiac Valve Diseases and Treatments (12 papers), Cardiovascular Function and Risk Factors (12 papers) and Congenital Heart Disease Studies (8 papers). Pavlo Yevtushenko collaborates with scholars based in Germany and United States. Pavlo Yevtushenko's co-authors include Leonid Goubergrits, Titus Küehne, Eugénie Riesenkampff, Ulrich Kertzscher, J. Schaller, Felix Berger, Marcus Kelm, Stephan Schubert, Anja Hennemuth and Jan Bruening and has published in prestigious journals such as Biophysical Journal, IEEE Transactions on Medical Imaging and Frontiers in Physiology.

In The Last Decade

Pavlo Yevtushenko

17 papers receiving 298 citations

Peers

Pavlo Yevtushenko

CCM

PRM

EPIDE

SURGE

RNMI

Simone Saitta Italy

Catriona Baker United Kingdom

Giorgia M. Bosi United Kingdom

João Filipe Fernandes United Kingdom

Rado Andriantsimiavona United Kingdom

Justin Tran United States

Haben Berhane United States

Selene Pirola United Kingdom

Christine M. Scotti United States

Merih Cibiş Netherlands

Simone Saitta Italy

Pavlo Yevtushenko

260 ×1.3

CCM

213 ×1.5

PRM

33 ×0.3

EPIDE

83 ×0.9

SURGE

79 ×1.8

RNMI

Citations per year, relative to Pavlo Yevtushenko Pavlo Yevtushenko (= 1×) peers Simone Saitta

Countries citing papers authored by Pavlo Yevtushenko

Since Specialization

Citations

This map shows the geographic impact of Pavlo Yevtushenko'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 Pavlo Yevtushenko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pavlo Yevtushenko more than expected).

Fields of papers citing papers by Pavlo Yevtushenko

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pavlo Yevtushenko. 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 Pavlo Yevtushenko. The network helps show where Pavlo Yevtushenko may publish in the future.

Co-authorship network of co-authors of Pavlo Yevtushenko

This figure shows the co-authorship network connecting the top 25 collaborators of Pavlo Yevtushenko. A scholar is included among the top collaborators of Pavlo Yevtushenko 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 Pavlo Yevtushenko. Pavlo Yevtushenko is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

Yevtushenko, Pavlo, Titus Küehne, Jan Bruening, & Leonid Goubergrits. (2025). A Simulation-Based Comparison of Human, Porcine and Ovine Pulmonary Artery Hemodynamics. Evaluating the Suitability of Large Animal Models for Endopulmonary Device Evaluation from a Hemodynamics Point of View. Cardiovascular Engineering and Technology. 16(6). 688–702. 1 indexed citations

Yevtushenko, Pavlo, et al.. (2024). Deep learning based assessment of hemodynamics in the coarctation of the aorta: comparison of bidirectional recurrent and convolutional neural networks. Frontiers in Physiology. 15. 1288339–1288339. 3 indexed citations

Yevtushenko, Pavlo, et al.. (2023). Modelling blood flow in patients with heart valve disease using deep learning: A computationally efficient method to expand diagnostic capabilities in clinical routine. Frontiers in Cardiovascular Medicine. 10. 1136935–1136935. 8 indexed citations

Yevtushenko, Pavlo, et al.. (2023). In-silico enhanced animal study of pulmonary artery pressure sensors: assessing hemodynamics using computational fluid dynamics. Frontiers in Cardiovascular Medicine. 10. 1193209–1193209. 3 indexed citations

Yevtushenko, Pavlo, Sarah Nordmeyer, Peter Krämer, et al.. (2022). Virtual treatment planning in three patients with univentricular physiology using computational fluid dynamics—Pitfalls and strategies. Frontiers in Cardiovascular Medicine. 9. 898701–898701. 3 indexed citations

Yevtushenko, Pavlo, Henryk Dreger, Axel Unbehaun, et al.. (2021). Computed Tomography-Based Assessment of Transvalvular Pressure Gradient in Aortic Stenosis. Frontiers in Cardiovascular Medicine. 8. 706628–706628. 10 indexed citations

Yevtushenko, Pavlo, Leonid Goubergrits, Arnaud A. A. Setio, et al.. (2021). Deep Learning Based Centerline-Aggregated Aortic Hemodynamics: An Efficient Alternative to Numerical Modeling of Hemodynamics. IEEE Journal of Biomedical and Health Informatics. 26(4). 1815–1825. 21 indexed citations

Thamsen, Bente, Pavlo Yevtushenko, Arnaud A. A. Setio, et al.. (2021). Synthetic Database of Aortic Morphometry and Hemodynamics: Overcoming Medical Imaging Data Availability. IEEE Transactions on Medical Imaging. 40(5). 1438–1449. 22 indexed citations

Yevtushenko, Pavlo, Jan Bruening, Sarah Nordmeyer, et al.. (2019). Surgical Aortic Valve Replacement: Are We Able to Improve Hemodynamic Outcome?. Biophysical Journal. 117(12). 2324–2336. 10 indexed citations

10.

Nordmeyer, Sarah, Pavlo Yevtushenko, Marcus Kelm, et al.. (2019). Abnormal aortic flow profiles persist after aortic valve replacement in the majority of patients with aortic valve disease: how model-based personalized therapy planning could improve results. A pilot study approach. European Journal of Cardio-Thoracic Surgery. 57(1). 133–141. 9 indexed citations

11.

Yevtushenko, Pavlo, et al.. (2018). Uncertainty Quantification for Non-invasive Assessment of Pressure Drop Across a Coarctation of the Aorta Using CFD. Cardiovascular Engineering and Technology. 9(4). 582–596. 18 indexed citations

12.

Yevtushenko, Pavlo, et al.. (2017). Numerical investigation of the impact of branching vessel boundary conditions on aortic hemodynamics. Current Directions in Biomedical Engineering. 3(2). 321–324. 2 indexed citations

13.

Nordmeyer, Sarah, Pavlo Yevtushenko, Jan Bruening, et al.. (2017). Hemodynamic Evaluation of a Biological and Mechanical Aortic Valve Prosthesis Using Patient‐Specific MRI‐Based CFD. Artificial Organs. 42(1). 49–57. 26 indexed citations

14.

Bruening, Jan, Pavlo Yevtushenko, Marcus Kelm, et al.. (2017). Impact of patient-specific LVOT inflow profiles on aortic valve prosthesis and ascending aorta hemodynamics. Journal of Computational Science. 24. 91–100. 16 indexed citations

15.

Goubergrits, Leonid, Eugénie Riesenkampff, Pavlo Yevtushenko, et al.. (2014). Is MRI-Based CFD Able to Improve Clinical Treatment of Coarctations of Aorta?. Annals of Biomedical Engineering. 43(1). 168–176. 25 indexed citations

16.

Goubergrits, Leonid, Eugénie Riesenkampff, Pavlo Yevtushenko, et al.. (2014). MRI‐based computational fluid dynamics for diagnosis and treatment prediction: Clinical validation study in patients with coarctation of aorta. Journal of Magnetic Resonance Imaging. 41(4). 909–916. 75 indexed citations

17.

Goubergrits, Leonid, Pavlo Yevtushenko, J. Schaller, et al.. (2013). The Impact of MRI-based Inflow for the Hemodynamic Evaluation of Aortic Coarctation. Annals of Biomedical Engineering. 41(12). 2575–2587. 52 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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