Tomasz Markiewicz

65 papers receiving 1.2k citations

Peers

Tomasz Markiewicz
Comparison fields: 5 of 126
  • Biophysics 147
  • Cardiology and Cardiovascular Medicine 394
  • Cognitive Neuroscience 315
  • Computer Vision and Pattern Recognition 299
  • Artificial Intelligence 427
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M. Muthu Rama Krishnan India
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Citations per year

Countries citing papers authored by Tomasz Markiewicz

Since Specialization
Citations

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

Fields of papers citing papers by Tomasz Markiewicz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004391
2 2019119
3 200886
4
MLP and SVM networks - a comparative study
200451
5 200551
6 200648
7 200745
8 201034
9 201531
10 201725
11 202123
12 201820
13 201120
14
Comparative analysis of methods for accurate recognition of cells through nuclei staining of Ki-67 in neuroblastoma and estrogen/progesterone status staining in breast cancer.
200920
15
Image processing for accurate cell recognition and count on histologic slides.
200619
16 201118
17 200414
18 201614
19 200613
20
Data mining techniques for feature selection in blood cell recognition
200612

About Tomasz Markiewicz

Tomasz Markiewicz is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Biomedical Engineering, having authored 70 papers that have together received 1.2k indexed citations. Recurring topics across this work include AI in cancer detection (27 papers), Radiomics and Machine Learning in Medical Imaging (11 papers), Cell Image Analysis Techniques (10 papers), Digital Imaging for Blood Diseases (10 papers), Medical Image Segmentation Techniques (9 papers), Renal cell carcinoma treatment (7 papers), Gene expression and cancer classification (6 papers) and Advanced X-ray and CT Imaging (5 papers). The work is most often cited by research in Biophysics (147 citations), Cardiology and Cardiovascular Medicine (394 citations), Cognitive Neuroscience (315 citations), Computer Vision and Pattern Recognition (299 citations) and Artificial Intelligence (427 citations). Tomasz Markiewicz has collaborated with scholars based in Poland, United States and Russia. Frequent co-authors include S. Osowski, Trần Hoài Linh, Krzysztof Siwek, Żaneta Świderska-Chadaj, Wojciech Kozłowski, Bartłomiej Grala, Szczepan Cierniak, J Słodkowska, K. Brudzewski and Arkadiusz Gertych. Their work appears in journals such as Diagnostic Pathology, Expert Systems with Applications, Journal of Applied Biomedicine, Scientific Reports and Journal of Microscopy.

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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