Georg Steinbuß
Impact in
- Health Informatics top 10%
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- Radiomics and Machine Learning in Medical Imaging
Papers in
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- AI in cancer detection 5
- Anomaly Detection Techniques and Applications 2
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- Radiomics and Machine Learning in Medical Imaging 3
- Co-authors
- Katharina Kriegsmann (7 shared papers)Mark Kriegsmann (7 shared papers)Christiane Zgorzelski (4 shared papers)Sascha Dietrich (1 shared paper)Matthias M. Gaida (2 shared papers)Alexander Brobeil (1 shared paper)Benjamin Goeppert (1 shared paper)Gunhild Mechtersheimer (1 shared paper)
- Journals
- Cancers (2 papers)International Journal of Molecular Sciences (2 papers)PROTEOMICS - CLINICAL APPLICATIONS (1 paper)Frontiers in Oncology (1 paper)Clinical and Translational Medicine (1 paper)
- Partner nations
- GermanyUnited StatesAustria
In The Last Decade
Georg Steinbuß
11 papers receiving 159 citations
Peers
Comparison fields: 5 of 42
- Health Informatics 11
- Radiology, Nuclear Medicine and Imaging 57
- Artificial Intelligence 70
- Oncology 43
- Cancer Research 13
Countries citing papers authored by Georg Steinbuß
This map shows the geographic impact of Georg Steinbuß'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 Georg Steinbuß with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Georg Steinbuß more than expected).
Fields of papers citing papers by Georg Steinbuß
This network shows the impact of papers produced by Georg Steinbuß. 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 Georg Steinbuß. The network helps show where Georg Steinbuß may publish in the future.
Co-authors
The 25 scholars most cited alongside Georg Steinbuß, 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 | 2021 | 50 | |
| 2 | 2021 | 30 | |
| 3 | 2020 | 21 | |
| 4 | 2022 | 17 | |
| 5 | 2022 | 13 | |
| 6 | 2022 | 13 | |
| 7 | 2023 | 6 | |
| 8 | 2019 | 6 | |
| 9 | 2017 | 3 | |
| 10 | 2019 | 3 | |
| 11 | 2020 | 1 |
About Georg Steinbuß
Georg Steinbuß is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Molecular Biology, Control and Systems Engineering and Oncology, having authored 11 papers that have together received 163 indexed citations. Recurring topics across this work include AI in cancer detection (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Anomaly Detection Techniques and Applications (2 papers), Fault Detection and Control Systems (2 papers), Molecular Biology Techniques and Applications (2 papers), Advanced Proteomics Techniques and Applications (1 paper), Pancreatic and Hepatic Oncology Research (1 paper) and Advanced Battery Technologies Research (1 paper). The work is most often cited by research in Health Informatics (11 citations), Radiology, Nuclear Medicine and Imaging (57 citations), Artificial Intelligence (70 citations), Oncology (43 citations) and Cancer Research (13 citations). Georg Steinbuß has collaborated with scholars based in Germany, United States and Austria. Frequent co-authors include Katharina Kriegsmann, Mark Kriegsmann, Christiane Zgorzelski, Sascha Dietrich, Matthias M. Gaida, Alexander Brobeil, Benjamin Goeppert, Gunhild Mechtersheimer, Jörg Kriegsmann and Thomas Muley. Their work appears in journals such as Cancers, International Journal of Molecular Sciences, PROTEOMICS - CLINICAL APPLICATIONS, Frontiers in Oncology and Clinical and Translational Medicine.
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.