Sergey Simakov

4.5k total citations
90 papers, 804 citations indexed

About

Sergey Simakov is a scholar working on Cardiology and Cardiovascular Medicine, Surgery and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Sergey Simakov has authored 90 papers receiving a total of 804 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Cardiology and Cardiovascular Medicine, 33 papers in Surgery and 21 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Sergey Simakov's work include Coronary Interventions and Diagnostics (22 papers), Cardiac Imaging and Diagnostics (16 papers) and Nuclear Physics and Applications (15 papers). Sergey Simakov is often cited by papers focused on Coronary Interventions and Diagnostics (22 papers), Cardiac Imaging and Diagnostics (16 papers) and Nuclear Physics and Applications (15 papers). Sergey Simakov collaborates with scholars based in Russia, China and United States. Sergey Simakov's co-authors include Yuri Vassilevski, Vitaly Volpert, Adélia Sequeira, N. M. Bessonov, Fuyou Liang, А. С. Холодов, U. Fischer, F. Yu. Kopylov, Philipp Kopylov and Xinyang Ge and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Journal of Biomechanics.

In The Last Decade

Sergey Simakov

85 papers receiving 774 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sergey Simakov Russia 15 293 274 152 115 115 90 804
Chris J. Elkins United States 8 224 0.8× 76 0.3× 423 2.8× 99 0.9× 45 0.4× 9 730
Kirby G. Vosburgh United States 19 28 0.1× 331 1.2× 184 1.2× 69 0.6× 218 1.9× 68 1.2k
Akihiro Haga Japan 15 223 0.8× 57 0.2× 558 3.7× 14 0.1× 224 1.9× 105 1.1k
Braden Goddard United States 12 75 0.3× 70 0.3× 137 0.9× 108 0.9× 47 0.4× 63 628
Hiroshi Tsutsui Japan 21 516 1.8× 348 1.3× 468 3.1× 83 0.7× 158 1.4× 143 1.5k
Walter G. O’Dell United States 18 368 1.3× 125 0.5× 709 4.7× 27 0.2× 332 2.9× 46 1.2k
Orlando Javier Soto Sandoval United States 17 122 0.4× 74 0.3× 61 0.4× 66 0.6× 50 0.4× 43 781
Ehud J. Schmidt United States 23 656 2.2× 180 0.7× 821 5.4× 21 0.2× 303 2.6× 90 1.5k
Aaron Fenster Canada 16 78 0.3× 76 0.3× 370 2.4× 36 0.3× 352 3.1× 58 861
Joseph Y. Cheng United States 22 248 0.8× 68 0.2× 1.3k 8.4× 18 0.2× 229 2.0× 55 1.9k

Countries citing papers authored by Sergey Simakov

Since Specialization
Citations

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

Fields of papers citing papers by Sergey Simakov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sergey Simakov

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

All Works

20 of 20 papers shown
1.
Li, Xuanyu, Zhi Zhang, Sergey Simakov, et al.. (2025). Influence of pressure guidewire on coronary hemodynamics and fractional flow reserve. Physics of Fluids. 37(3). 2 indexed citations
2.
Lurie, Fedor, et al.. (2025). Thigh muscle pump function during ambulation. Journal of Vascular Surgery Venous and Lymphatic Disorders. 13(4). 102248–102248. 1 indexed citations
3.
4.
Lurie, Fedor, et al.. (2024). The human lower leg muscle pump functions as a flow diverter pump, maintaining low ambulatory venous pressures during locomotion. Journal of Vascular Surgery Venous and Lymphatic Disorders. 13(1). 101996–101996. 5 indexed citations
5.
Исаев, А. П., et al.. (2024). Physically Informed Deep Learning Technique for Estimating Blood Flow Parameters in Four-Vessel Junction after the Fontan Procedure. Computation. 12(3). 41–41. 8 indexed citations
6.
Li, Xuanyu, et al.. (2023). The Influence of Aortic Valve Disease on Coronary Hemodynamics: A Computational Model-Based Study. Bioengineering. 10(6). 709–709. 1 indexed citations
7.
8.
Trkov, Andrej, R. Capote, D. Bernard, et al.. (2023). Progress in the Evaluation and Validation of n+56,57Fe Cross Sections. EPJ Web of Conferences. 284. 12002–12002. 1 indexed citations
9.
Liang, Fuyou, et al.. (2023). Myocardial perfusion segmentation and partitioning methods in personalized models of coronary blood flow. Russian Journal of Numerical Analysis and Mathematical Modelling. 38(5). 293–302.
10.
Simakov, Sergey, et al.. (2023). Validation of boundary conditions for coronary circulation model based on a lumped parameter approach. Russian Journal of Numerical Analysis and Mathematical Modelling. 38(3). 161–172. 1 indexed citations
11.
Simakov, Sergey, et al.. (2021). Computational Analysis of Haemodynamic Indices in Synthetic Atherosclerotic Coronary Netwroks. Mathematics. 9(18). 2221–2221. 4 indexed citations
12.
Lurie, Fedor, et al.. (2021). Blood flow from competent tributaries is likely contributor to distally increasing reflux volume in incompetent great saphenous vein. Journal of Vascular Surgery Venous and Lymphatic Disorders. 10(1). 69–74. 2 indexed citations
13.
Ge, Xinyang, Youjun Liu, Zhaofang Yin, et al.. (2020). Comparison of Instantaneous Wave-Free Ratio (iFR) and Fractional Flow Reserve (FFR) with respect to Their Sensitivities to Cardiovascular Factors: A Computational Model-Based Study. Journal of Interventional Cardiology. 2020. 1–12. 13 indexed citations
14.
Kopylov, Philipp, et al.. (2020). Computational Analysis of Coronary Blood Flow: The Role of Asynchronous Pacing and Arrhythmias. Mathematics. 8(8). 1205–1205. 15 indexed citations
15.
Simakov, Sergey, et al.. (2020). Non-invasive fractional flow reserve: a comparison of one-dimensional and three-dimensional mathematical modeling effectiveness. SHILAP Revista de lepidopterología. 19(2). 2303–2303. 3 indexed citations
16.
Ge, Xinyang, Youjun Liu, Shengxian Tu, et al.. (2019). Model‐based analysis of the sensitivities and diagnostic implications of FFR and CFR under various pathological conditions. International Journal for Numerical Methods in Biomedical Engineering. 37(11). e3257–e3257. 22 indexed citations
17.
Carson, Jason, Sanjay Pant, Carl Roobottom, et al.. (2019). Non‐invasive coronary CT angiography‐derived fractional flow reserve: A benchmark study comparing the diagnostic performance of four different computational methodologies. International Journal for Numerical Methods in Biomedical Engineering. 35(10). e3235–e3235. 39 indexed citations
18.
Kopylov, F. Yu., et al.. (2017). MATHEMATICAL MODELLING OF CIRCULATION IN EXTRACRANIAL BRACHOCEPHALIC ARTERIES AT P RE-OPERATION STAGE IN CAROTID ENDARTERECTOMY. Russian Journal of Cardiology. 88–92. 5 indexed citations
19.
Kopylov, F. Yu., et al.. (2017). Asymptomatic atherosclerosis of the brachiocephalic arteries: Current approaches to diagnosis and treatment. Terapevticheskii arkhiv. 89(4). 95–100. 9 indexed citations
20.
Carlson, A.D., V.G. Pronyaev, R. Capote, et al.. (2016). Toward a New Evaluation of Neutron Standards. Springer Link (Chiba Institute of Technology).

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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