Frank Krämer
Impact in
- Health Informatics top 5%
- Cancer Research top 10%
- MicroRNA in disease regulation
Papers in
-
- Bioinformatics and Genomic Networks 16
- Gene expression and cancer classification 7
- Biomedical Text Mining and Ontologies 6
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- AI in cancer detection 5
- Co-authors
- Dominik Müller (15 shared papers)Iñaki Soto‐Rey (11 shared papers)Tim Beißbarth (23 shared papers)Steffen J. Glaser (9 shared papers)Marian Grade (14 shared papers)Jochen Gaedcke (13 shared papers)Annalen Bleckmann (6 shared papers)Melanie Spitzner (8 shared papers)
- Journals
- Journal of Magnetic Resonance (6 papers)Cancer Research (3 papers)Carcinogenesis (2 papers)Journal of Biomedical Informatics (2 papers)Bioinformatics (2 papers)
- Partner nations
- GermanyUnited StatesSpain
In The Last Decade
Frank Krämer
80 papers receiving 2.5k citations
Frank Krämer's Hit Papers
Peers
Comparison fields: 5 of 176
- Health Informatics 43
- Cancer Research 261
- Radiology, Nuclear Medicine and Imaging 368
- Oncology 414
- Molecular Biology 1.0k
Countries citing papers authored by Frank Krämer
This map shows the geographic impact of Frank Krämer'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 Frank Krämer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank Krämer more than expected).
Fields of papers citing papers by Frank Krämer
This network shows the impact of papers produced by Frank Krämer. 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 Frank Krämer. The network helps show where Frank Krämer may publish in the future.
Co-authors
The 25 scholars most cited alongside Frank Krämer, 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 88 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Towards a guideline for evaluation metrics in medical image segmentation Hit paper breakdown → | 2022 | 344 |
| 2 | 2011 | 129 | |
| 3 | 2004 | 111 | |
| 4 | 2012 | 111 | |
| 5 | 2010 | 109 | |
| 6 | 2013 | 108 | |
| 7 | 2017 | 104 | |
| 8 | 2021 | 101 | |
| 9 | 2021 | 82 | |
| 10 | 2008 | 80 | |
| 11 | 2021 | 75 | |
| 12 | 2011 | 75 | |
| 13 | 2022 | 71 | |
| 14 | 2010 | 67 | |
| 15 | 2020 | 66 | |
| 16 | 2015 | 64 | |
| 17 | 2013 | 61 | |
| 18 | 2012 | 60 | |
| 19 | 2019 | 50 | |
| 20 | 2004 | 42 |
About Frank Krämer
Frank Krämer is a scholar working on Molecular Biology, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Spectroscopy and Nuclear and High Energy Physics, having authored 88 papers that have together received 2.5k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (16 papers), Advanced NMR Techniques and Applications (8 papers), Gene expression and cancer classification (7 papers), COVID-19 diagnosis using AI (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), NMR spectroscopy and applications (6 papers), Biomedical Text Mining and Ontologies (6 papers) and AI in cancer detection (5 papers). The work is most often cited by research in Health Informatics (43 citations), Cancer Research (261 citations), Radiology, Nuclear Medicine and Imaging (368 citations), Oncology (414 citations) and Molecular Biology (1.0k citations). Frank Krämer has collaborated with scholars based in Germany, United States and Spain. Frequent co-authors include Dominik Müller, Iñaki Soto‐Rey, Tim Beißbarth, Steffen J. Glaser, Marian Grade, Jochen Gaedcke, Annalen Bleckmann, Melanie Spitzner, Steven A. Johnsen and Thomas Ried. Their work appears in journals such as Journal of Magnetic Resonance, Cancer Research, Carcinogenesis, Journal of Biomedical Informatics and Bioinformatics.
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.