Mark Kohn

968 citations
8 papers · 829 · h-index 6

Impact in

Papers in

Mark Kohn

7 papers receiving 783 citations

Peers

Mark Kohn
Comparison fields: 5 of 98
  • Radiology, Nuclear Medicine and Imaging 309
  • Cognitive Neuroscience 241
  • Psychiatry and Mental health 169
  • Neurology 63
  • Computer Vision and Pattern Recognition 121
Replace Sun I. Kim with:
Sun I. Kim South Korea
R. Kikinis United States
Jun Ki Lee South Korea
Xiaoying Tang China
Benjamin Billot United States
Robert Donnino United States
Andrea D. Klunder United States
Can Ceritoglu United States
R. Allom United Kingdom
Anil Rao United Kingdom
Mark Kohn relative to Sun I. Kim South Korea Sun I. Kim's profile →
Citations per field
00.5×1.5×
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Citations per year

Countries citing papers authored by Mark Kohn

Since Specialization
Citations

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

Fields of papers citing papers by Mark Kohn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mark Kohn, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mark Kohn Line = papers co-authored together Mark Kohn links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 1991389
2 1991248
3 1991123
4 200633
5 199429
6 20115
7 20032
8 20200

About Mark Kohn

Mark Kohn is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Cognitive Neuroscience, Surgery and Cardiology and Cardiovascular Medicine, having authored 8 papers that have together received 829 indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (3 papers), Advanced Neuroimaging Techniques and Applications (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Orthopedic Surgery and Rehabilitation (1 paper), Medical Image Segmentation Techniques (1 paper), Cognitive Abilities and Testing (1 paper), Digital Image Processing Techniques (1 paper) and Schizophrenia research and treatment (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (309 citations), Cognitive Neuroscience (241 citations), Psychiatry and Mental health (169 citations), Neurology (63 citations) and Computer Vision and Pattern Recognition (121 citations). Mark Kohn has collaborated with scholars based in United States and Japan. Frequent co-authors include Ruben C. Gur, P. David Mozley, Susan M. Resnick, Nipul Tanna, R A Zimmerman, Gábor T. Herman, Robert L. Grossman, Gary Gottlieb, Susan J. Atlas and Robert A. Zimmerman. Their work appears in journals such as Radiology, Proceedings of the National Academy of Sciences, Skeletal Radiology, Schizophrenia Research and Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.

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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