Michail Mamalakis

43 total papers · 472 total citations
18 papers, 239 citations indexed

About

Michail Mamalakis is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Computer Vision and Pattern Recognition. According to data from OpenAlex, Michail Mamalakis has authored 18 papers receiving a total of 239 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Cardiology and Cardiovascular Medicine and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Michail Mamalakis's work include Cardiac Imaging and Diagnostics (5 papers), COVID-19 diagnosis using AI (4 papers) and COVID-19 Clinical Research Studies (3 papers). Michail Mamalakis is often cited by papers focused on Cardiac Imaging and Diagnostics (5 papers), COVID-19 diagnosis using AI (4 papers) and COVID-19 Clinical Research Studies (3 papers). Michail Mamalakis collaborates with scholars based in United Kingdom, Netherlands and Greece. Michail Mamalakis's co-authors include Abhirup Banerjee, Surajit Ray, Bart Vorselaars, Louise S. Mackenzie, Mark Baker, Andrew J. Swift, Pankaj Garg, Samer Alabed, Jim M. Wild and Michael Sharkey and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Radiology.

In The Last Decade

Michail Mamalakis

17 papers receiving 233 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Michail Mamalakis	156	69	55	37	36	18	239
Yang Liu	191 1.2×	74 1.1×	27 0.5×	41 1.1×	14 0.4×	19	312
Zeno Falaschi	157 1.0×	42 0.6×	66 1.2×	21 0.6×	32 0.9×	18	257
Sagar Kulkarni	151 1.0×	59 0.9×	31 0.6×	80 2.2×	45 1.3×	23	323
Shravya Shetty	166 1.1×	67 1.0×	24 0.4×	72 1.9×	33 0.9×	15	267
Liyan Pan	95 0.6×	89 1.3×	13 0.2×	32 0.9×	10 0.3×	18	277
David Bermejo-Peláez	173 1.1×	54 0.8×	33 0.6×	11 0.3×	51 1.4×	19	329
Guilherme Silva	166 1.1×	111 1.6×	13 0.2×	35 0.9×	25 0.7×	18	327
Rajagopala Chadaga	107 0.7×	133 1.9×	15 0.3×	38 1.0×	25 0.7×	21	281
Tin Lok Chiu	194 1.2×	116 1.7×	16 0.3×	43 1.2×	13 0.4×	21	319
Samer Albahra	78 0.5×	108 1.6×	33 0.6×	70 1.9×	41 1.1×	15	313

Countries citing papers authored by Michail Mamalakis

Since Specialization

Citations

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

Fields of papers citing papers by Michail Mamalakis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michail Mamalakis

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

All Works

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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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