Mikhail Kagan

1.0k total citations
18 papers, 560 citations indexed

About

Mikhail Kagan is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Mikhail Kagan has authored 18 papers receiving a total of 560 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Molecular Biology and 4 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Mikhail Kagan's work include Cardiac Imaging and Diagnostics (10 papers), Advanced MRI Techniques and Applications (8 papers) and Medical Imaging Techniques and Applications (6 papers). Mikhail Kagan is often cited by papers focused on Cardiac Imaging and Diagnostics (10 papers), Advanced MRI Techniques and Applications (8 papers) and Medical Imaging Techniques and Applications (6 papers). Mikhail Kagan collaborates with scholars based in United States, Germany and Russia. Mikhail Kagan's co-authors include Ming Yu, Simon P. Robinson, Michael Azure, Heike Radeke, Ajay Purohit, David S. Casebier, Mary Guaraldi, Padmaja Yalamanchili, Mahesh Mistry and Jennifer L. McDonald and has published in prestigious journals such as Journal of the American College of Cardiology, Journal of Medicinal Chemistry and Bioconjugate Chemistry.

In The Last Decade

Mikhail Kagan

18 papers receiving 539 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 Kagan United States 11 417 123 70 54 41 18 560
Jinsong Xia United States 9 139 0.3× 100 0.8× 89 1.3× 29 0.5× 51 1.2× 14 315
Thomas Buettner Germany 12 202 0.5× 23 0.2× 60 0.9× 25 0.5× 48 1.2× 13 462
Kim Gunnar Toft Norway 11 171 0.4× 31 0.3× 47 0.7× 26 0.5× 111 2.7× 19 346
Mirta Ruiz United States 17 515 1.2× 260 2.1× 62 0.9× 155 2.9× 27 0.7× 35 753
Daniela Di Lisi Italy 15 120 0.3× 436 3.5× 121 1.7× 73 1.4× 10 0.2× 59 607
Charles A. Maitz United States 9 241 0.6× 34 0.3× 42 0.6× 21 0.4× 125 3.0× 28 370
Jayanta Bordoloi United Kingdom 8 80 0.2× 15 0.1× 56 0.8× 31 0.6× 9 0.2× 14 243
Kathleen W. Zhang United States 12 119 0.3× 310 2.5× 164 2.3× 36 0.7× 8 0.2× 24 480
Kenneth N. Giedd United States 11 111 0.3× 65 0.5× 180 2.6× 104 1.9× 6 0.1× 18 504

Countries citing papers authored by Mikhail Kagan

Since Specialization
Citations

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

Fields of papers citing papers by Mikhail Kagan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mikhail Kagan

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

All Works

18 of 18 papers shown
1.
Kagan, Mikhail, et al.. (2018). Autosomal Dominant Tubulo-Interstitial Kidney Disease Due to MUC1 Mutation. Review and case report. 20(2). 225–229. 1 indexed citations
2.
Kagan, Mikhail. (2016). Acute Post-Streptococcal Glomerulonephritis in Children. Вопросы современной педиатрии. 15(1). 25–32. 1 indexed citations
3.
Yu, Ming, Mikhail Kagan, Mary Guaraldi, et al.. (2013). Cardiac retention of PET neuronal imaging agent LMI1195 in different species: Impact of norepinephrine uptake-1 and -2 transporters. Nuclear Medicine and Biology. 40(5). 682–688. 17 indexed citations
4.
Yu, Ming, et al.. (2012). LMI1195 PET imaging in evaluation of regional cardiac sympathetic denervation and its potential role in antiarrhythmic drug treatment. European Journal of Nuclear Medicine and Molecular Imaging. 39(12). 1910–1919. 19 indexed citations
5.
Yu, Ming, Mary Guaraldi, Paula Silva, et al.. (2011). Evaluation of LMI1195, a Novel 18 F-Labeled Cardiac Neuronal PET Imaging Agent, in Cells and Animal Models. Circulation Cardiovascular Imaging. 4(4). 435–443. 79 indexed citations
6.
Radeke, Heike, Ajay Purohit, Thomas D. Harris, et al.. (2011). Synthesis and Cardiac Imaging of18F-Ligands Selective for β1-Adrenoreceptors. ACS Medicinal Chemistry Letters. 2(9). 650–655. 9 indexed citations
7.
Guaraldi, Mary, Paula Silva, Mikhail Kagan, et al.. (2010). LMI1195: A NEW 18F BENZYLGUANIDINE ANALOG FOR PET CARDIAC SYMPATHETIC NEURONAL IMAGING. Journal of the American College of Cardiology. 55(10). A88.E832–A88.E832. 1 indexed citations
8.
Yu, Ming, et al.. (2010). Cardiac imaging and safety evaluation of BMS747158, a novel PET myocardial perfusion imaging agent, in chronic myocardial compromised rabbits. Journal of Nuclear Cardiology. 17(4). 631–636. 19 indexed citations
9.
Yu, Ming, Mary Guaraldi, Mikhail Kagan, et al.. (2009). Effects of food intake and anesthetic on cardiac imaging and uptake of BMS747158-02 in comparison with FDG. Journal of Nuclear Cardiology. 16(5). 763–768. 7 indexed citations
10.
Purohit, Ajay, Heike Radeke, Michael Azure, et al.. (2008). Synthesis and Biological Evaluation of Pyridazinone Analogues as Potential Cardiac Positron Emission Tomography Tracers. Journal of Medicinal Chemistry. 51(10). 2954–2970. 33 indexed citations
11.
Yu, Ming, Mary Guaraldi, Mikhail Kagan, et al.. (2008). Assessment of 18F-labeled mitochondrial complex I inhibitors as PET myocardial perfusion imaging agents in rats, rabbits, and primates. European Journal of Nuclear Medicine and Molecular Imaging. 36(1). 63–72. 33 indexed citations
12.
Purohit, Ajay, Mary Guaraldi, Mikhail Kagan, et al.. (2007). Quinazoline derivatives as MC-I inhibitors: Evaluation of myocardial uptake using Positron Emission Tomography in rat and non-human primate. Bioorganic & Medicinal Chemistry Letters. 17(17). 4882–4885. 15 indexed citations
13.
Yalamanchili, Padmaja, Ming Yu, Mikhail Kagan, et al.. (2007). Mechanism of uptake and retention of F-18 BMS-747158-02 in cardiomyocytes: A novel PET myocardial imaging agent. Journal of Nuclear Cardiology. 14(6). 782–788. 113 indexed citations
14.
Yu, Ming, Mary Guaraldi, Mahesh Mistry, et al.. (2007). BMS-747158-02: A novel PET myocardial perfusion imaging agent. Journal of Nuclear Cardiology. 14(6). 789–798. 111 indexed citations
15.
Kagan, Mikhail, Arthur H. Cohen, Verena Matejas, Christopher N. Vlangos, & Martin Zenker. (2007). A milder variant of Pierson syndrome. Pediatric Nephrology. 23(2). 323–327. 38 indexed citations
16.
Radeke, Heike, Padmaja Yalamanchili, Zhiqin Zhang, et al.. (2007). Synthesis and Biological Evaluation of the Mitochondrial Complex 1 Inhibitor 2-[4-(4-Fluorobutyl)benzylsulfanyl]-3-methylchromene-4-one as a Potential Cardiac Positron Emission Tomography Tracer. Journal of Medicinal Chemistry. 50(18). 4304–4315. 9 indexed citations
17.
Lazewatsky, Joel, et al.. (2003). The effect of dilution medium on the measurement of in-vitro properties of ultrasound contrast agents. 2. 1737–1742. 2 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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