Marek Wodziński
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- AI in cancer detection 19
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- Radiomics and Machine Learning in Medical Imaging 14
- COVID-19 diagnosis using AI 4
- Co-authors
- Andrzej Skalski (13 shared papers)Henning Müller (14 shared papers)Daria Hemmerling (13 shared papers)Tommaso Banzato (9 shared papers)Juan Rafael Orozco‐Arroyave (2 shared papers)Elmar Nöth (1 shared paper)Manfredo Atzori (10 shared papers)Alessandro Zotti (7 shared papers)
- Journals
- Scientific Reports (6 papers)Computer Methods and Programs in Biomedicine (5 papers)Sensors (5 papers)Frontiers in Veterinary Science (2 papers)Research in Veterinary Science (2 papers)
- Partner nations
- PolandSwitzerlandItaly
In The Last Decade
Marek Wodziński
44 papers receiving 486 citations
Peers
Comparison fields: 5 of 77
- Health Informatics 50
- Radiology, Nuclear Medicine and Imaging 142
- Biophysics 38
- Artificial Intelligence 167
- Signal Processing 42
Countries citing papers authored by Marek Wodziński
This map shows the geographic impact of Marek Wodziński'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 Marek Wodziński with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marek Wodziński more than expected).
Fields of papers citing papers by Marek Wodziński
This network shows the impact of papers produced by Marek Wodziński. 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 Marek Wodziński. The network helps show where Marek Wodziński may publish in the future.
Co-authors
The 25 scholars most cited alongside Marek Wodziński, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 83 | |
| 2 | 2021 | 45 | |
| 3 | 2022 | 43 | |
| 4 | 2025 | 29 | |
| 5 | 2023 | 28 | |
| 6 | 2020 | 22 | |
| 7 | 2019 | 22 | |
| 8 | 2021 | 21 | |
| 9 | 2022 | 20 | |
| 10 | 2024 | 19 | |
| 11 | 2021 | 13 | |
| 12 | 2020 | 12 | |
| 13 | 2023 | 10 | |
| 14 | 2020 | 10 | |
| 15 | 2023 | 8 | |
| 16 | 2018 | 8 | |
| 17 | 2020 | 7 | |
| 18 | 2024 | 7 | |
| 19 | 2020 | 7 | |
| 20 | 2023 | 6 |
About Marek Wodziński
Marek Wodziński is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Biomedical Engineering and Pulmonary and Respiratory Medicine, having authored 50 papers that have together received 500 indexed citations. Recurring topics across this work include AI in cancer detection (19 papers), Radiomics and Machine Learning in Medical Imaging (14 papers), Digital Imaging for Blood Diseases (6 papers), Advanced Radiotherapy Techniques (5 papers), COVID-19 diagnosis using AI (4 papers), Medical Imaging and Analysis (4 papers), Voice and Speech Disorders (4 papers) and Traumatic Brain Injury and Neurovascular Disturbances (3 papers). The work is most often cited by research in Health Informatics (50 citations), Radiology, Nuclear Medicine and Imaging (142 citations), Biophysics (38 citations), Artificial Intelligence (167 citations) and Signal Processing (42 citations). Marek Wodziński has collaborated with scholars based in Poland, Switzerland and Italy. Frequent co-authors include Andrzej Skalski, Henning Müller, Daria Hemmerling, Tommaso Banzato, Juan Rafael Orozco‐Arroyave, Elmar Nöth, Manfredo Atzori, Alessandro Zotti, Silvia Burti and Niccolò Marini. Their work appears in journals such as Scientific Reports, Computer Methods and Programs in Biomedicine, Sensors, Frontiers in Veterinary Science and Research in Veterinary Science.
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.