Marie Kearns

11 total papers · 1.6k total citations
7 papers, 1.1k citations indexed

About

Marie Kearns is a scholar working on Surgery, Pulmonary and Respiratory Medicine and Internal Medicine. According to data from OpenAlex, Marie Kearns has authored 7 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Surgery, 1 paper in Pulmonary and Respiratory Medicine and 1 paper in Internal Medicine. Recurrent topics in Marie Kearns's work include Surgical Simulation and Training (2 papers), Reconstructive Surgery and Microvascular Techniques (2 papers) and Orthopedic Surgery and Rehabilitation (2 papers). Marie Kearns is often cited by papers focused on Surgical Simulation and Training (2 papers), Reconstructive Surgery and Microvascular Techniques (2 papers) and Orthopedic Surgery and Rehabilitation (2 papers). Marie Kearns collaborates with scholars based in United Kingdom, United States and Singapore. Marie Kearns's co-authors include Heather M. Niemeier, Rena R. Wing, Kittichai Promrat, David E. Kleiner, Jack R. Wands, Joseph L. Fava, Simon Myers, Ali Ghanem, Vinay Kumar Singh and Panayotis N. Soucacos and has published in prestigious journals such as Hepatology, Injury and Scandinavian Journal of Surgery.

In The Last Decade

Marie Kearns

7 papers receiving 1.1k citations

Hit Papers

Randomized Controlled Tri... 2009 2026 2014 2020 2009 250 500 750

Author Peers

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

Author Last Decade Papers Cites
Marie Kearns 946 597 313 268 260 7 1.1k
Mariano Marino 1.0k 1.1× 533 0.9× 277 0.9× 205 0.8× 149 0.6× 5 1.2k
Federica Scaglioni 1.0k 1.1× 555 0.9× 296 0.9× 177 0.7× 147 0.6× 9 1.2k
Diane Biernacki 1.2k 1.3× 733 1.2× 368 1.2× 248 0.9× 237 0.9× 9 1.4k
Emanuela Fagà 929 1.0× 544 0.9× 166 0.5× 236 0.9× 136 0.5× 7 1.0k
Hassan Azhari 1.1k 1.2× 453 0.8× 393 1.3× 200 0.7× 215 0.8× 17 1.3k
Takahisa Eguchi 759 0.8× 348 0.6× 321 1.0× 332 1.2× 185 0.7× 18 1.1k
Elnaz Ehteshami Afshar 1.1k 1.2× 449 0.8× 368 1.2× 196 0.7× 269 1.0× 10 1.4k
Jian-Gao Fan 907 1.0× 381 0.6× 324 1.0× 123 0.5× 156 0.6× 5 1.2k
Dawn M. Emick 788 0.8× 337 0.6× 471 1.5× 116 0.4× 256 1.0× 7 1.2k
E. Gentilcore 1.2k 1.3× 577 1.0× 530 1.7× 184 0.7× 169 0.7× 6 1.3k

Countries citing papers authored by Marie Kearns

Since Specialization
Citations

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

Fields of papers citing papers by Marie Kearns

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marie Kearns

This figure shows the co-authorship network connecting the top 25 collaborators of Marie Kearns. A scholar is included among the top collaborators of Marie Kearns 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 Marie Kearns. Marie Kearns 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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