John Sharko

8 papers receiving 309 citations

Peers

John Sharko
Comparison fields: 5 of 64
  • Cancer Research 47
  • Health Informatics 4
  • Pathology and Forensic Medicine 47
  • Computer Vision and Pattern Recognition 60
  • Health Information Management 12
Replace Miguel Henriques Abreu with:
Miguel Henriques Abreu Portugal
Nimrod Rappoport Israel
Bernard Omolo United States
Aidan N. Gomez United States
Sepideh Babaei Germany
Deborah Thompson United States
Dimitrios Kleftogiannis Saudi Arabia
Vincent Peter C. Magboo Philippines
Takashi Takao Japan
Yuxin Zheng China
John Sharko relative to Miguel Henriques Abreu Portugal Miguel Henriques Abreu's profile →
Citations per field
00.5×
Miguel Henriques Abreu · 1×
Citations per year

Countries citing papers authored by John Sharko

Since Specialization
Citations

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

Fields of papers citing papers by John Sharko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside John Sharko, 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 John Sharko Line = papers co-authored together John Sharko links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 201293
2 201288
3 200858
4 200945
5 200713
6 200912
7 20074
8
Radviz extensions with applications
20091

About John Sharko

John Sharko is a scholar working on Molecular Biology, Information Systems, Artificial Intelligence, Pathology and Forensic Medicine and Pediatrics, Perinatology and Child Health, having authored 8 papers that have together received 314 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (2 papers), Data Mining Algorithms and Applications (2 papers), Gene expression and cancer classification (1 paper), Morphological variations and asymmetry (1 paper), Cancer Risks and Factors (1 paper), Data Visualization and Analytics (1 paper), BRCA gene mutations in cancer (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Cancer Research (47 citations), Health Informatics (4 citations), Pathology and Forensic Medicine (47 citations), Computer Vision and Pattern Recognition (60 citations) and Health Information Management (12 citations). John Sharko has collaborated with scholars based in United States and Switzerland. Frequent co-authors include Georges Grinstein, Kenneth A. Marx, Kevin S. Hughes, Michele A. Gadd, Ahmet Korkut Bellı, Fernanda Polubriaginof, Constance A. Roche, Michelle C. Specht, Judy E. Garber and Julliette M. Buckley. Their work appears in journals such as Journal of Pathology Informatics, Breast Cancer Research and Treatment, IEEE Transactions on Visualization and Computer Graphics and The Breast Journal.

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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