Norman Zerbe
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
- Biophysics top 5%
- Cell Image Analysis Techniques
Papers in
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- AI in cancer detection 24
- Explainable Artificial Intelligence (XAI) 3
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- Radiomics and Machine Learning in Medical Imaging 11
- Co-authors
- Peter Hufnagl (18 shared papers)Harshita Sharma (8 shared papers)Olaf Hellwich (8 shared papers)Tim‐Rasmus Kiehl (8 shared papers)Markus Plass (5 shared papers)Christian Geißler (5 shared papers)Rita Carvalho (6 shared papers)Michaela Kargl (4 shared papers)
In The Last Decade
Norman Zerbe
30 papers receiving 843 citations
Peers
Comparison fields: 5 of 95
- Health Informatics 101
- Biophysics 94
- Artificial Intelligence 521
- Radiology, Nuclear Medicine and Imaging 288
- Computer Vision and Pattern Recognition 202
Countries citing papers authored by Norman Zerbe
This map shows the geographic impact of Norman Zerbe'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 Norman Zerbe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Norman Zerbe more than expected).
Fields of papers citing papers by Norman Zerbe
This network shows the impact of papers produced by Norman Zerbe. 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 Norman Zerbe. The network helps show where Norman Zerbe may publish in the future.
Co-authors
The 25 scholars most cited alongside Norman Zerbe, 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 252 | |
| 2 | 2022 | 93 | |
| 3 | 2012 | 84 | |
| 4 | 2021 | 74 | |
| 5 | 2023 | 54 | |
| 6 | 2015 | 50 | |
| 7 | 2015 | 39 | |
| 8 | 2011 | 30 | |
| 9 | 2012 | 28 | |
| 10 | 2021 | 27 | |
| 11 | 2023 | 22 | |
| 12 | 2017 | 11 | |
| 13 | 2024 | 11 | |
| 14 | 2015 | 11 | |
| 15 | 2022 | 11 | |
| 16 | 2016 | 10 | |
| 17 | 2017 | 8 | |
| 18 | 2021 | 7 | |
| 19 | 2016 | 7 | |
| 20 | 2017 | 6 |
About Norman Zerbe
Norman Zerbe is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Health Informatics and Molecular Biology, having authored 37 papers that have together received 866 indexed citations. Recurring topics across this work include AI in cancer detection (24 papers), Radiomics and Machine Learning in Medical Imaging (11 papers), Artificial Intelligence in Healthcare and Education (9 papers), Image Retrieval and Classification Techniques (4 papers), Digital Imaging for Blood Diseases (3 papers), Biomedical Text Mining and Ontologies (3 papers), Explainable Artificial Intelligence (XAI) (3 papers) and Medical Image Segmentation Techniques (2 papers). The work is most often cited by research in Health Informatics (101 citations), Biophysics (94 citations), Artificial Intelligence (521 citations), Radiology, Nuclear Medicine and Imaging (288 citations) and Computer Vision and Pattern Recognition (202 citations). Norman Zerbe has collaborated with scholars based in Germany, Italy and France. Frequent co-authors include Peter Hufnagl, Harshita Sharma, Olaf Hellwich, Tim‐Rasmus Kiehl, Markus Plass, Christian Geißler, Rita Carvalho, Michaela Kargl, Andreas Holzinger and Heimo Müller. Their work appears in journals such as Diagnostic Pathology, Journal of Pathology Informatics, Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin, Laboratory Investigation and Future Generation Computer Systems.
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.