К. V. Zavadovsky

779 total citations
83 papers, 332 citations indexed

About

К. V. Zavadovsky is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Surgery. According to data from OpenAlex, К. V. Zavadovsky has authored 83 papers receiving a total of 332 indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Radiology, Nuclear Medicine and Imaging, 46 papers in Cardiology and Cardiovascular Medicine and 23 papers in Surgery. Recurrent topics in К. V. Zavadovsky's work include Cardiac Imaging and Diagnostics (58 papers), Advanced X-ray and CT Imaging (18 papers) and Advanced MRI Techniques and Applications (15 papers). К. V. Zavadovsky is often cited by papers focused on Cardiac Imaging and Diagnostics (58 papers), Advanced X-ray and CT Imaging (18 papers) and Advanced MRI Techniques and Applications (15 papers). К. V. Zavadovsky collaborates with scholars based in Russia, United States and Italy. К. V. Zavadovsky's co-authors include А. В. Мочула, Lishmanov IuB, Alessia Gimelli, Riccardo Liga, A Boshchenko, Е. А. Нестеров, A. V. Vrublevsky, С. В. Попов, V. V. Ryabov and Peter R. Oeltgen and has published in prestigious journals such as SHILAP Revista de lepidopterología, European Heart Journal and Pflügers Archiv - European Journal of Physiology.

In The Last Decade

К. V. Zavadovsky

64 papers receiving 308 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
К. V. Zavadovsky Russia 9 258 166 83 79 11 83 332
Serge Van Kriekinge United States 4 300 1.2× 115 0.7× 59 0.7× 126 1.6× 5 0.5× 7 322
Mischa T. Rijnierse Netherlands 9 188 0.7× 170 1.0× 70 0.8× 34 0.4× 21 1.9× 25 260
M. Cerqueira Portugal 3 297 1.2× 127 0.8× 70 0.8× 120 1.5× 13 1.2× 7 328
Gilbert Wijntjens Netherlands 9 124 0.5× 172 1.0× 131 1.6× 26 0.3× 9 0.8× 21 235
R Folks United States 5 289 1.1× 89 0.5× 33 0.4× 110 1.4× 16 1.5× 6 312
Giovanni Monizzi Italy 7 179 0.7× 160 1.0× 136 1.6× 38 0.5× 30 2.7× 22 243
Leonardo Sara Brazil 4 285 1.1× 121 0.7× 91 1.1× 117 1.5× 29 2.6× 6 304
Jan C.J. Netherlands 10 129 0.5× 277 1.7× 57 0.7× 24 0.3× 4 0.4× 17 307
Felix Keng Singapore 7 195 0.8× 163 1.0× 46 0.6× 45 0.6× 3 0.3× 16 252
Juan Miguel Sánchez‐Gómez Spain 13 68 0.3× 298 1.8× 48 0.6× 25 0.3× 12 1.1× 28 372

Countries citing papers authored by К. V. Zavadovsky

Since Specialization
Citations

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

Fields of papers citing papers by К. V. Zavadovsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by К. V. Zavadovsky. 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 К. V. Zavadovsky. The network helps show where К. V. Zavadovsky may publish in the future.

Co-authorship network of co-authors of К. V. Zavadovsky

This figure shows the co-authorship network connecting the top 25 collaborators of К. V. Zavadovsky. A scholar is included among the top collaborators of К. V. Zavadovsky 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 К. V. Zavadovsky. К. V. Zavadovsky 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.
Ryabov, V. V., et al.. (2025). Assessing coronary microvascular dysfunction in refractory no-reflow: Insights from dynamic myocardial perfusion scintigraphy and cardiac MRI. Microvascular Research. 162. 104862–104862. 1 indexed citations
2.
Koshelskaya, О. A., et al.. (2025). Visceral adipose tissue according to magnetic resonance imaging as a factor associated with leptin resistance in stable coronary artery disease. CARDIOVASCULAR THERAPY AND PREVENTION. 24(1). 4236–4236.
3.
Суслова, Т. Е., et al.. (2024). Quantitative computed tomography coronary angiography in patients with acute myocardial infarction: association with cardiac biomarkers. SHILAP Revista de lepidopterología. 29(12). 6101–6101.
4.
Shelkovnikova, Tatyana A., et al.. (2023). Cardiac MRI Radiomics: review. Siberian Journal of Clinical and Experimental Medicine. 38(3). 13–22. 1 indexed citations
5.
Мочула, А. В., et al.. (2023). Significance of inflammation markers in patients with coronary microvascular dysfunction and non-obstructive coronary artery disease. SHILAP Revista de lepidopterología. 28(6). 5399–5399.
6.
Мочула, А. В., et al.. (2023). Heart failure with preserved ejection fraction: the role of microvascular dysfunction. SHILAP Revista de lepidopterología. 21(4). 88–97.
7.
Мочула, А. В., et al.. (2023). Association of Calcium Index and Myocardial Blood Flow in Non-Obstructive Atherosclerotic Lesion of the Coronary Arteries. Annals of the Russian academy of medical sciences. 78(2). 85–95.
8.
Мочула, А. В., et al.. (2023). State of the art mathematical methods of the coronary blood flow modelling: background and clinical value. Kardiologiia. 63(3). 77–84. 1 indexed citations
9.
10.
Мочула, А. В., et al.. (2022). Low-dose dobutamine stress gated blood pool SPECT assessment of left ventricular contractile reserve in ischemic cardiomyopathy: a feasibility study. European Journal of Nuclear Medicine and Molecular Imaging. 49(7). 2219–2231. 2 indexed citations
11.
Мочула, А. В., et al.. (2022). Combined myocardial perfusion scintigraphy and computed tomography: diagnostic and prognostic value in coronary artery disease. SHILAP Revista de lepidopterología. 27(6). 4925–4925. 1 indexed citations
12.
Мочула, А. В., et al.. (2022). The role of microvascular dysfunction in the pathogenesis of heart failure with preserved efficiency fraction. Kazan medical journal. 103(6). 918–927. 2 indexed citations
13.
Мочула, А. В., et al.. (2022). Role of humoral markers in the pathogenesis of heart failure with preserved ejection fraction in patients with non-obstructive coronary artery disease. SHILAP Revista de lepidopterología. 27(10). 5162–5162. 4 indexed citations
14.
Мочула, А. В., et al.. (2021). Modern scintigraphic methods for assessing myocardial blood flow and reserve. SHILAP Revista de lepidopterología. 20(1). 178–189. 1 indexed citations
15.
16.
Zavadovsky, К. V., et al.. (2020). 123 I-MIBG scintigraphy in the assessment of heart failure prognosis and effectiveness of cardiac resynchronization therapy. Kardiologiia. 60(2). 122–130. 3 indexed citations
17.
18.
Zavadovsky, К. V., A. V. Vrublevsky, N. V. Naryzhnaya, et al.. (2020). Takotsubo Syndrome: Clinical Manifestations, Etiology and Pathogenesis. Current Cardiology Reviews. 17(2). 188–203. 13 indexed citations
19.
Karas, S. I., et al.. (2019). Virtual patients with cardiovascular pathology: technology for postgraduate medical education. CARDIOVASCULAR THERAPY AND PREVENTION. 18(6). 51–56. 2 indexed citations
20.
Zavadovsky, К. V., et al.. (2018). 3D PRINTING IN PREOPERATIVE ASSESSMENT OF CARDIAC ANATOMY IN PATIENT WITH CONGENITAL VENTRICULAR SEPTAL DEFECT AND DOUBLE-CHAMBERED RIGHT VENTRICLE. Russian Electronic Journal of Radiology. 8(1). 194–201. 3 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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