Talent Shevchenko

573 total citations
8 papers, 465 citations indexed

About

Talent Shevchenko is a scholar working on Biomedical Engineering, Materials Chemistry and Social Psychology. According to data from OpenAlex, Talent Shevchenko has authored 8 papers receiving a total of 465 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Biomedical Engineering, 3 papers in Materials Chemistry and 2 papers in Social Psychology. Recurrent topics in Talent Shevchenko's work include Ultrasound and Hyperthermia Applications (4 papers), Photoacoustic and Ultrasonic Imaging (4 papers) and Ultrasound and Cavitation Phenomena (3 papers). Talent Shevchenko is often cited by papers focused on Ultrasound and Hyperthermia Applications (4 papers), Photoacoustic and Ultrasonic Imaging (4 papers) and Ultrasound and Cavitation Phenomena (3 papers). Talent Shevchenko collaborates with scholars based in United States, Belgium and France. Talent Shevchenko's co-authors include Alexander L. Klibanov, Chien Ting Chin, Balasundar I. Raju, Ralf Seip, Ryoichi Teruyama, William E. Armstrong, M.R. Böhmer, Ceciel Chlon, Joseph C. Callaway and Jakub Toczek and has published in prestigious journals such as Journal of Neurophysiology, Journal of Controlled Release and European Heart Journal.

In The Last Decade

Talent Shevchenko

8 papers receiving 455 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Talent Shevchenko United States 7 286 114 112 104 80 8 465
Megan Rich United States 12 147 0.5× 71 0.6× 126 1.1× 55 0.5× 78 1.0× 18 439
Yingjiang Liu China 8 245 0.9× 89 0.8× 40 0.4× 130 1.3× 34 0.4× 13 374
Stuart Ibsen United States 7 459 1.6× 166 1.5× 82 0.7× 101 1.0× 83 1.0× 9 594
Ahad A. Rahim United Kingdom 10 213 0.7× 109 1.0× 175 1.6× 59 0.6× 34 0.4× 21 534
Jonas Franz Germany 14 56 0.2× 50 0.4× 115 1.0× 31 0.3× 44 0.6× 30 576
Tada‐aki Kudo Japan 15 113 0.4× 48 0.4× 165 1.5× 33 0.3× 34 0.4× 39 442
Kiran Bhattacharyya United States 10 219 0.8× 85 0.7× 57 0.5× 35 0.3× 46 0.6× 24 414
Marcella Wyatt United Kingdom 18 124 0.4× 20 0.2× 225 2.0× 74 0.7× 159 2.0× 22 724
Mohammed Rahman United States 7 81 0.3× 36 0.3× 109 1.0× 37 0.4× 21 0.3× 9 446
Dezhuang Ye United States 16 469 1.6× 170 1.5× 85 0.8× 216 2.1× 73 0.9× 32 725

Countries citing papers authored by Talent Shevchenko

Since Specialization
Citations

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

Fields of papers citing papers by Talent Shevchenko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Talent Shevchenko

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

All Works

8 of 8 papers shown
1.
Hernot, Sophie, Sunil Unnikrishnan, Talent Shevchenko, et al.. (2012). Nanobody-coupled microbubbles as novel molecular tracer.. European Heart Journal. 33. 403–404. 1 indexed citations
2.
Rychak, Joshua J., Peter B. Ernst, Prasad Konkalmatt, et al.. (2012). Ultrasound-based molecular imaging and specific gene delivery to mesenteric vasculature by endothelial adhesion molecule targeted microbubbles in a mouse model of Crohn's disease. Journal of Controlled Release. 165(3). 216–225. 59 indexed citations
3.
Hernot, Sophie, Sunil Unnikrishnan, Talent Shevchenko, et al.. (2011). Nanobody-coupled microbubbles as novel molecular tracer. Journal of Controlled Release. 158(2). 346–353. 80 indexed citations
4.
Klibanov, Alexander L., Talent Shevchenko, Balasundar I. Raju, Ralf Seip, & Chien Ting Chin. (2010). Ultrasound-triggered release of materials entrapped in microbubble–liposome constructs: A tool for targeted drug delivery. Journal of Controlled Release. 148(1). 13–17. 144 indexed citations
5.
Böhmer, M.R., Ceciel Chlon, Balasundar I. Raju, et al.. (2010). Focused ultrasound and microbubbles for enhanced extravasation. Journal of Controlled Release. 148(1). 18–24. 79 indexed citations
6.
Chin, Chien Ting, Balasundar I. Raju, Talent Shevchenko, & Alexander L. Klibanov. (2009). Control and reversal of tumor growth by ultrasound activated microbubbles. 77–80. 18 indexed citations
7.
Shevchenko, Talent, Ryoichi Teruyama, & William E. Armstrong. (2004). High-Threshold, Kv3-Like Potassium Currents in Magnocellular Neurosecretory Neurons and Their Role in Spike Repolarization. Journal of Neurophysiology. 92(5). 3043–3055. 26 indexed citations
8.
Callaway, Joseph C., et al.. (2003). AHP's, HAP's and DAP's: How Potassium Currents Regulate the Excitability of Rat Supraoptic Neurones. Journal of Computational Neuroscience. 15(3). 367–389. 58 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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