Katarzyna Borys
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
- Medical Imaging Techniques and Applications
Papers in
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- Machine Learning in Healthcare 2
- Explainable Artificial Intelligence (XAI) 2
- AI in cancer detection 1
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- Artificial Intelligence in Healthcare and Education 2
- Co-authors
- Felix Nensa (13 shared papers)Christoph M. Friedrich (6 shared papers)Christin Seifert (2 shared papers)Nicole C. Krämer (2 shared papers)Meike Nauta (2 shared papers)René Hosch (11 shared papers)Sven Koitka (3 shared papers)Giulia Baldini (4 shared papers)
- Journals
- Investigative Radiology (3 papers)Journal of Medical Internet Research (2 papers)European Journal of Radiology (2 papers)Blood (1 paper)BMC Health Services Research (1 paper)
- Partner nations
- GermanyNetherlandsSwitzerland
In The Last Decade
Katarzyna Borys
9 papers receiving 203 citations
Peers
Comparison fields: 5 of 59
- Health Informatics 60
- Radiology, Nuclear Medicine and Imaging 73
- Artificial Intelligence 97
- Health Information Management 9
- Neurology 15
Countries citing papers authored by Katarzyna Borys
This map shows the geographic impact of Katarzyna Borys'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 Katarzyna Borys with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Katarzyna Borys more than expected).
Fields of papers citing papers by Katarzyna Borys
This network shows the impact of papers produced by Katarzyna Borys. 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 Katarzyna Borys. The network helps show where Katarzyna Borys may publish in the future.
Co-authors
The 25 scholars most cited alongside Katarzyna Borys, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 100 | |
| 2 | 2023 | 76 | |
| 3 | 2023 | 13 | |
| 4 | 2023 | 7 | |
| 5 | 2025 | 4 | |
| 6 | 2024 | 3 | |
| 7 | 2025 | 1 | |
| 8 | 2025 | 1 | |
| 9 | 2025 | 1 | |
| 10 | 2025 | 0 | |
| 11 | 2025 | 0 | |
| 12 | 2025 | 0 | |
| 13 | 2025 | 0 |
About Katarzyna Borys
Katarzyna Borys is a scholar working on Artificial Intelligence, Health Informatics, Molecular Biology, Epidemiology and Applied Psychology, having authored 13 papers that have together received 206 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (2 papers), Machine Learning in Healthcare (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Digital Mental Health Interventions (1 paper), Hospital Admissions and Outcomes (1 paper), Radiomics and Machine Learning in Medical Imaging (1 paper), Nutrition and Health in Aging (1 paper) and AI in cancer detection (1 paper). The work is most often cited by research in Health Informatics (60 citations), Radiology, Nuclear Medicine and Imaging (73 citations), Artificial Intelligence (97 citations), Health Information Management (9 citations) and Neurology (15 citations). Katarzyna Borys has collaborated with scholars based in Germany, Netherlands and Switzerland. Frequent co-authors include Felix Nensa, Christoph M. Friedrich, Christin Seifert, Nicole C. Krämer, Meike Nauta, René Hosch, Sven Koitka, Giulia Baldini, Péter Horn and Amin T. Turki. Their work appears in journals such as Investigative Radiology, Journal of Medical Internet Research, European Journal of Radiology, Blood and BMC Health Services Research.
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.