Revaz Machaidze

892 total citations
7 papers, 675 citations indexed

About

Revaz Machaidze is a scholar working on Biomaterials, Genetics and Biomedical Engineering. According to data from OpenAlex, Revaz Machaidze has authored 7 papers receiving a total of 675 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Biomaterials, 3 papers in Genetics and 3 papers in Biomedical Engineering. Recurrent topics in Revaz Machaidze's work include Nanoparticle-Based Drug Delivery (5 papers), Glioma Diagnosis and Treatment (3 papers) and Characterization and Applications of Magnetic Nanoparticles (2 papers). Revaz Machaidze is often cited by papers focused on Nanoparticle-Based Drug Delivery (5 papers), Glioma Diagnosis and Treatment (3 papers) and Characterization and Applications of Magnetic Nanoparticles (2 papers). Revaz Machaidze collaborates with scholars based in United States, Greece and China. Revaz Machaidze's co-authors include Milota Kaluzová, Hui Mao, Li‐Ya Wang, Albert J. Schuette, Costas G. Hadjipanayis, Hongwei Chen, Xinying Wu, Costas G. Hadjipanayis, Alexandros Bouras and Sandro Santagata and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Cancer Research and Neurosurgery.

In The Last Decade

Revaz Machaidze

7 papers receiving 668 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Revaz Machaidze United States 6 338 313 191 170 96 7 675
Costas G. Hadjipanayis United States 6 250 0.7× 225 0.7× 139 0.7× 124 0.7× 66 0.7× 8 571
Qi Yue China 14 126 0.4× 282 0.9× 270 1.4× 99 0.6× 54 0.6× 32 776
Marc Schwarz Germany 13 208 0.6× 246 0.8× 125 0.7× 104 0.6× 35 0.4× 29 760
Achuthamangalam B. Madhankumar United States 13 206 0.6× 208 0.7× 345 1.8× 114 0.7× 21 0.2× 19 791
Margaret F. Bennewitz United States 12 173 0.5× 180 0.6× 178 0.9× 148 0.9× 30 0.3× 29 762
Liejing Lu China 19 234 0.7× 412 1.3× 262 1.4× 103 0.6× 28 0.3× 36 933
Hemant Sarin United States 10 375 1.1× 325 1.0× 389 2.0× 104 0.6× 22 0.2× 20 1.1k
Yu Xuan Koo Singapore 10 151 0.4× 162 0.5× 208 1.1× 79 0.5× 150 1.6× 14 700
Daniel Golovko United States 19 193 0.6× 361 1.2× 217 1.1× 165 1.0× 24 0.3× 21 917
Aharon Ocherashvilli Israel 8 175 0.5× 146 0.5× 200 1.0× 202 1.2× 24 0.3× 9 689

Countries citing papers authored by Revaz Machaidze

Since Specialization
Citations

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

Fields of papers citing papers by Revaz Machaidze

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Revaz Machaidze

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

All Works

7 of 7 papers shown
1.
Machaidze, Revaz, et al.. (2016). Novel technology for the fast production of complex nanoliposomes. 16(4). 172–176. 1 indexed citations
2.
Kaluzová, Milota, Alexandros Bouras, Revaz Machaidze, & Costas G. Hadjipanayis. (2015). Targeted therapy of glioblastoma stem-like cells and tumor non-stem cells using cetuximab-conjugated iron-oxide nanoparticles. Oncotarget. 6(11). 8788–8806. 115 indexed citations
3.
Calligaris, David, Daniel R. Feldman, Isaiah Norton, et al.. (2015). MALDI mass spectrometry imaging analysis of pituitary adenomas for near-real-time tumor delineation. Proceedings of the National Academy of Sciences. 112(32). 9978–9983. 60 indexed citations
4.
Du, Ziming, Malak Abedalthagafi, Ayal A. Aizer, et al.. (2014). Increased expression of the immune modulatory molecule PD-L1 (CD274) in anaplastic meningioma. Oncotarget. 6(7). 4704–4716. 126 indexed citations
5.
Platt, Simon R., Edjah K. Nduom, Marc Kent, et al.. (2012). Canine Model of Convection-Enhanced Delivery of Cetuximab-Conjugated Iron-Oxide Nanoparticles Monitored With Magnetic Resonance Imaging. Neurosurgery. 59(Supplement 1). 107–113. 33 indexed citations
6.
Khurshid, Hafsa, Costas G. Hadjipanayis, Hongwei Chen, et al.. (2012). Core/shell structured iron/iron-oxide nanoparticles as excellent MRI contrast enhancement agents. Journal of Magnetism and Magnetic Materials. 331. 17–20. 27 indexed citations
7.
Hadjipanayis, Costas G., Revaz Machaidze, Milota Kaluzová, et al.. (2010). EGFRvIII Antibody–Conjugated Iron Oxide Nanoparticles for Magnetic Resonance Imaging–Guided Convection-Enhanced Delivery and Targeted Therapy of Glioblastoma. Cancer Research. 70(15). 6303–6312. 313 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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