Peter Dankerl
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Radiomics and Machine Learning in Medical Imaging 6
- Radiation Dose and Imaging 4
- Cardiac Imaging and Diagnostics 3
- Radiology practices and education 3
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- Breast Lesions and Carcinomas 4
- Co-authors
- Michael Uder (29 shared papers)Matthias Hammon (19 shared papers)Alexander Cavallaro (14 shared papers)Rolf Janka (11 shared papers)Alexey Tsymbal (5 shared papers)Michael Suehling (2 shared papers)Matthias Stefan May (3 shared papers)Erwin S. Schultz (1 shared paper)
In The Last Decade
Peter Dankerl
34 papers receiving 374 citations
Peers
Comparison fields: 5 of 48
- Health Informatics 33
- Radiology, Nuclear Medicine and Imaging 97
- Immunology 56
- Computer Vision and Pattern Recognition 62
- Orthopedics and Sports Medicine 21
Countries citing papers authored by Peter Dankerl
This map shows the geographic impact of Peter Dankerl'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 Peter Dankerl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Dankerl more than expected).
Fields of papers citing papers by Peter Dankerl
This network shows the impact of papers produced by Peter Dankerl. 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 Peter Dankerl. The network helps show where Peter Dankerl may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Dankerl, 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 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 77 | |
| 2 | 2013 | 49 | |
| 3 | 2013 | 26 | |
| 4 | 2013 | 26 | |
| 5 | 2016 | 21 | |
| 6 | 2014 | 19 | |
| 7 | 2021 | 19 | |
| 8 | 2017 | 16 | |
| 9 | 2016 | 15 | |
| 10 | 2014 | 13 | |
| 11 | 2017 | 9 | |
| 12 | 2012 | 8 | |
| 13 | 2013 | 8 | |
| 14 | 2013 | 7 | |
| 15 | 2015 | 7 | |
| 16 | 2018 | 6 | |
| 17 | 2014 | 5 | |
| 18 | 2014 | 5 | |
| 19 | 2014 | 5 | |
| 20 | 2017 | 5 |
About Peter Dankerl
Peter Dankerl is a scholar working on Radiology, Nuclear Medicine and Imaging, Pathology and Forensic Medicine, Computer Vision and Pattern Recognition, Health Informatics and Pulmonary and Respiratory Medicine, having authored 34 papers that have together received 386 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), Radiation Dose and Imaging (4 papers), Medical Image Segmentation Techniques (4 papers), Breast Lesions and Carcinomas (4 papers), Medical Imaging and Analysis (3 papers), Cardiac Imaging and Diagnostics (3 papers), Radiology practices and education (3 papers) and Artificial Intelligence in Healthcare and Education (2 papers). The work is most often cited by research in Health Informatics (33 citations), Radiology, Nuclear Medicine and Imaging (97 citations), Immunology (56 citations), Computer Vision and Pattern Recognition (62 citations) and Orthopedics and Sports Medicine (21 citations). Peter Dankerl has collaborated with scholars based in Germany, Belgium and Singapore. Frequent co-authors include Michael Uder, Matthias Hammon, Alexander Cavallaro, Rolf Janka, Alexey Tsymbal, Michael Suehling, Matthias Stefan May, Erwin S. Schultz, Gerold Schuler and Stefanie Groß. Their work appears in journals such as RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, Academic Radiology, International Journal of Computer Assisted Radiology and Surgery, Journal of Imaging Informatics in Medicine and Clinical Neuroradiology.
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.