John Tomaszeweski

13 total papers · 729 total citations
12 papers, 587 citations indexed

About

John Tomaszeweski is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Pulmonary and Respiratory Medicine. According to data from OpenAlex, John Tomaszeweski has authored 12 papers receiving a total of 587 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 4 papers in Pulmonary and Respiratory Medicine. Recurrent topics in John Tomaszeweski's work include AI in cancer detection (10 papers), Medical Image Segmentation Techniques (8 papers) and Prostate Cancer Diagnosis and Treatment (4 papers). John Tomaszeweski is often cited by papers focused on AI in cancer detection (10 papers), Medical Image Segmentation Techniques (8 papers) and Prostate Cancer Diagnosis and Treatment (4 papers). John Tomaszeweski collaborates with scholars based in United States and Netherlands. John Tomaszeweski's co-authors include Anant Madabhushi, Michael D. Feldman, Scott Doyle, Michaël Feldman, Deborah J. Chute, Dimitris Metaxas, Christos Davatzikos, Yiqiang Zhan, Dinggang Shen and Mark Rosen and has published in prestigious journals such as IEEE Transactions on Medical Imaging, Lecture notes in computer science and Academic Radiology.

In The Last Decade

John Tomaszeweski

12 papers receiving 571 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 Tomaszeweski 349 309 239 130 107 12 587
Matthias Elter 405 1.2× 236 0.8× 230 1.0× 90 0.7× 69 0.6× 26 618
Hussain Fatakdawala 177 0.5× 135 0.4× 200 0.8× 64 0.5× 166 1.6× 19 525
Sebastian Otálora 292 0.8× 198 0.6× 342 1.4× 41 0.3× 73 0.7× 18 510
Kunal Nagpal 342 1.0× 108 0.3× 257 1.1× 106 0.8× 62 0.6× 10 589
Wei Yang 397 1.1× 177 0.6× 283 1.2× 48 0.4× 36 0.3× 17 536
Pingjun Chen 277 0.8× 170 0.6× 236 1.0× 28 0.2× 79 0.7× 22 614
Arash Mohtashamian 385 1.1× 86 0.3× 312 1.3× 119 0.9× 58 0.5× 11 565
Lichao Wang 389 1.1× 243 0.8× 232 1.0× 34 0.3× 69 0.6× 9 684
Monjoy Saha 369 1.1× 171 0.6× 267 1.1× 45 0.3× 39 0.4× 18 553
Lily H. Peng 443 1.3× 94 0.3× 373 1.6× 131 1.0× 67 0.6× 6 682

Countries citing papers authored by John Tomaszeweski

Since Specialization
Citations

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

Fields of papers citing papers by John Tomaszeweski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Tomaszeweski

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