Mikhail Chmelevsky

482 total citations
38 papers, 327 citations indexed

About

Mikhail Chmelevsky is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Cognitive Neuroscience. According to data from OpenAlex, Mikhail Chmelevsky has authored 38 papers receiving a total of 327 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Cardiology and Cardiovascular Medicine, 10 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Cognitive Neuroscience. Recurrent topics in Mikhail Chmelevsky's work include Cardiac Arrhythmias and Treatments (25 papers), Cardiac electrophysiology and arrhythmias (24 papers) and Cardiac pacing and defibrillation studies (14 papers). Mikhail Chmelevsky is often cited by papers focused on Cardiac Arrhythmias and Treatments (25 papers), Cardiac electrophysiology and arrhythmias (24 papers) and Cardiac pacing and defibrillation studies (14 papers). Mikhail Chmelevsky collaborates with scholars based in Russia, Germany and Portugal. Mikhail Chmelevsky's co-authors include Danila Potyagaylo, Christine Lemeš, Д. С. Лебедев, Karl‐Heinz Kück, Erik Wißner, А. Ш. Ревишвили, Sebastian Deiß, Tilman Maurer, Andreas Metzner and Anne-Lise Hachulla and has published in prestigious journals such as Frontiers in Physiology, Journal of the American Heart Association and Journal of Clinical Medicine.

In The Last Decade

Mikhail Chmelevsky

31 papers receiving 310 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mikhail Chmelevsky Russia 10 302 57 20 20 15 38 327
Kavit A. Desouza United States 7 278 0.9× 47 0.8× 37 1.9× 8 0.4× 10 0.7× 11 320
Uyên Châu Nguyên Netherlands 10 269 0.9× 48 0.8× 6 0.3× 46 2.3× 7 0.5× 33 283
Stefan Asbach Germany 11 269 0.9× 54 0.9× 10 0.5× 21 1.1× 3 0.2× 34 316
Sarah W.E. Baalman Netherlands 10 288 1.0× 23 0.4× 14 0.7× 7 0.3× 14 0.9× 22 320
Norman Qureshi United Kingdom 15 924 3.1× 63 1.1× 29 1.4× 54 2.7× 26 1.7× 74 967
Fujian Qu United States 9 302 1.0× 49 0.9× 20 1.0× 15 0.8× 10 0.7× 29 364
F J Chorro Spain 8 375 1.2× 39 0.7× 25 1.3× 5 0.3× 14 0.9× 27 395
Greg Walcott United States 10 383 1.3× 27 0.5× 32 1.6× 4 0.2× 15 1.0× 17 419
Fabian Noti Switzerland 14 380 1.3× 17 0.3× 9 0.5× 16 0.8× 4 0.3× 58 420
Mary F. Otterness United States 5 772 2.6× 13 0.2× 14 0.7× 24 1.2× 10 0.7× 7 796

Countries citing papers authored by Mikhail Chmelevsky

Since Specialization
Citations

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

Fields of papers citing papers by Mikhail Chmelevsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mikhail Chmelevsky

This figure shows the co-authorship network connecting the top 25 collaborators of Mikhail Chmelevsky. A scholar is included among the top collaborators of Mikhail Chmelevsky 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 Mikhail Chmelevsky. Mikhail Chmelevsky 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.
Parreira, Leonor, Pedro Carmo, Sílvia Nunes, et al.. (2023). Electrocardiographic imaging to guide ablation of ventricular arrhythmias and agreement between two different systems. Journal of Electrocardiology. 80. 143–150. 4 indexed citations
2.
Chmelevsky, Mikhail, et al.. (2023). Clinical Validation of the New 12-Lead ECG Noninvasive Panoramic Epi-endocardial Mapping Technology. Computing in cardiology. 50. 1 indexed citations
3.
Chmelevsky, Mikhail, et al.. (2023). An Ensemble of Machine Learning Models for Multilabel Classification of Cardiovascular Diseases by ECGs. Computing in cardiology. 1 indexed citations
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5.
Chmelevsky, Mikhail, et al.. (2023). Clinical evaluation of the new 12-lead ECG noninvasive epi-endocardial mapping technology. EP Europace. 25(Supplement_1). 2 indexed citations
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Zweerink, Alwin, Danila Potyagaylo, Carine Stettler, et al.. (2021). His-Optimized Cardiac Resynchronization Therapy With Ventricular Fusion Pacing for Electrical Resynchronization in Heart Failure. JACC. Clinical electrophysiology. 7(7). 881–892. 41 indexed citations
9.
Stanevich, Oksana V., Mikhail Chmelevsky, N. A. Аrsentieva, et al.. (2021). A Novel Approach for COVID-19 Patient Condition Tracking: From Instant Prediction to Regular Monitoring. Frontiers in Medicine. 8. 744652–744652. 7 indexed citations
10.
Parreira, Leonor, Pedro Carmo, Pedro Adragão, et al.. (2020). Electrocardiographic imaging (ECGI): What is the minimal number of leads needed to obtain a good spatial resolution?. Journal of Electrocardiology. 62. 86–93. 14 indexed citations
11.
Potyagaylo, Danila, et al.. (2019). Single-Layer Based Algorithms for Solving the Inverse Problem of ECG. Computing in Cardiology Conference. 1–4. 1 indexed citations
12.
Chmelevsky, Mikhail, et al.. (2019). Noninvasive Electrocardiographic Imaging with Magnetic Resonance Tomography in Candidates for Cardiac Resynchronization Therapy. Computing in Cardiology Conference. 1–4. 1 indexed citations
13.
Potyagaylo, Danila, et al.. (2019). ECG Adapted Fastest Route Algorithm to Localize the Ectopic Excitation Origin in CRT Patients. Frontiers in Physiology. 10. 183–183. 15 indexed citations
14.
Potyagaylo, Danila, et al.. (2019). Combination of lead-field theory with cardiac vector direction: ECG imaging of septal ventricular activation. Journal of Electrocardiology. 57. S40–S44. 9 indexed citations
15.
Chmelevsky, Mikhail, et al.. (2018). Clinical Evaluation of Noninvasive ECGI Epi-Endocardial Mapping Accuracy. Computing in cardiology. 45. 9 indexed citations
16.
Chmelevsky, Mikhail, et al.. (2018). ECGI in atrial fibrillation: A clinician's wish list. Journal of Electrocardiology. 51(6). S88–S91. 6 indexed citations
17.
Wißner, Erik, et al.. (2018). Noninvasive Phase Mapping of Atrial Flutter in Humans – Comparison with Invasive Mapping. 4(1). 15–15. 1 indexed citations
18.
Wißner, Erik, et al.. (2017). Mapping of ventricular arrhythmias using a novel noninvasive epicardial and endocardial electrophysiology system. Journal of Electrocardiology. 51(1). 92–98. 19 indexed citations
19.
Wißner, Erik, А. Ш. Ревишвили, Andreas Metzner, et al.. (2016). Noninvasive epicardial and endocardial mapping of premature ventricular contractions. EP Europace. 19(5). euw103–euw103. 41 indexed citations
20.
Ревишвили, А. Ш., Erik Wißner, Д. С. Лебедев, et al.. (2015). Validation of the mapping accuracy of a novel non-invasive epicardial and endocardial electrophysiology system. EP Europace. 17(8). 1282–1288. 61 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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