John J. Gisvold

23 total papers · 1.2k total citations
21 papers, 842 citations indexed

About

John J. Gisvold is a scholar working on Pathology and Forensic Medicine, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, John J. Gisvold has authored 21 papers receiving a total of 842 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Pathology and Forensic Medicine, 6 papers in Artificial Intelligence and 6 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in John J. Gisvold's work include Breast Lesions and Carcinomas (9 papers), Breast Cancer Treatment Studies (6 papers) and AI in cancer detection (6 papers). John J. Gisvold is often cited by papers focused on Breast Lesions and Carcinomas (9 papers), Breast Cancer Treatment Studies (6 papers) and AI in cancer detection (6 papers). John J. Gisvold collaborates with scholars based in United States, Switzerland and Vietnam. John J. Gisvold's co-authors include Karl N. Krecke, Thomas B. Crotty, Lynn C. Hartmann, Rafaël Fonseca, Ivy A. Petersen, Ruth E. Johnson, J. F. Greenleaf, R. C. Bahn, J S Schreiman and Sandhya Pruthi and has published in prestigious journals such as Annals of Internal Medicine, Radiology and The American Journal of Surgical Pathology.

In The Last Decade

John J. Gisvold

21 papers receiving 794 citations

Author Peers

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

Author Last Decade Papers Cites
John J. Gisvold 428 342 260 182 154 21 842
In Ae Park 390 0.9× 300 0.9× 332 1.3× 155 0.9× 114 0.7× 28 883
Selin Çarkaci 295 0.7× 342 1.0× 357 1.4× 239 1.3× 89 0.6× 37 911
Paula B. Gordon 442 1.0× 318 0.9× 253 1.0× 358 2.0× 216 1.4× 38 939
Ellen Shaw de Paredes 334 0.8× 231 0.7× 188 0.7× 217 1.2× 203 1.3× 30 717
Susan Koelliker 496 1.2× 414 1.2× 337 1.3× 162 0.9× 238 1.5× 13 1.0k
I. Schreer 504 1.2× 390 1.1× 392 1.5× 184 1.0× 243 1.6× 51 922
Ines Gruber 298 0.7× 349 1.0× 204 0.8× 265 1.5× 64 0.4× 39 759
Yung‐Feng Lo 289 0.7× 317 0.9× 362 1.4× 199 1.1× 144 0.9× 46 815
Eleanor Cornford 349 0.8× 407 1.2× 220 0.8× 252 1.4× 171 1.1× 38 868
Alexis V. Nees 464 1.1× 394 1.2× 403 1.6× 159 0.9× 440 2.9× 33 1.0k

Countries citing papers authored by John J. Gisvold

Since Specialization
Citations

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

Fields of papers citing papers by John J. Gisvold

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John J. Gisvold. 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 John J. Gisvold. The network helps show where John J. Gisvold may publish in the future.

Co-authorship network of co-authors of John J. Gisvold

This figure shows the co-authorship network connecting the top 25 collaborators of John J. Gisvold. A scholar is included among the top collaborators of John J. Gisvold 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 John J. Gisvold. John J. Gisvold 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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