Fabian Both
Impact in
- Health Informatics top 10%
- Artificial Intelligence top 5%
- AI in cancer detection
- Domain Adaptation and Few-Shot Learning
Papers in
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- Multimodal Machine Learning Applications 2
- Advanced Image and Video Retrieval Techniques 1
- Co-authors
- Achim Rettinger (2 shared papers)Marc T. P. Adam (1 shared paper)Beat Peter Müller-Stich (1 shared paper)Klaus Hermann Maier-Hein (1 shared paper)Christof Weinhardt (1 shared paper)Manuel Wiesenfarth (1 shared paper)Sebastian Bodenstedt (1 shared paper)Fabian Isensee (1 shared paper)
In The Last Decade
Fabian Both
5 papers receiving 430 citations
Fabian Both's Hit Papers
Peers
Comparison fields: 5 of 46
- Health Informatics 19
- Artificial Intelligence 362
- Biophysics 49
- Radiology, Nuclear Medicine and Imaging 170
- Computer Vision and Pattern Recognition 168
Countries citing papers authored by Fabian Both
This map shows the geographic impact of Fabian Both'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 Fabian Both with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabian Both more than expected).
Fields of papers citing papers by Fabian Both
This network shows the impact of papers produced by Fabian Both. 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 Fabian Both. The network helps show where Fabian Both may publish in the future.
Co-authors
The 16 scholars most cited alongside Fabian Both, 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 | From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge Hit paper breakdown → | 2018 | 406 |
| 2 | 2017 | 23 | |
| 3 | 2018 | 12 | |
| 4 | 2016 | 4 | |
| 5 | 2017 | 1 |
About Fabian Both
Fabian Both is a scholar working on General Decision Sciences, Computer Vision and Pattern Recognition, Safety Research, Artificial Intelligence and Management Science and Operations Research, having authored 5 papers that have together received 446 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (2 papers), Advanced Image and Video Retrieval Techniques (1 paper), Game Theory and Applications (1 paper), Radiomics and Machine Learning in Medical Imaging (1 paper), Experimental Behavioral Economics Studies (1 paper), Domain Adaptation and Few-Shot Learning (1 paper), Topic Modeling (1 paper) and Lung Cancer Diagnosis and Treatment (1 paper). The work is most often cited by research in Health Informatics (19 citations), Artificial Intelligence (362 citations), Biophysics (49 citations), Radiology, Nuclear Medicine and Imaging (170 citations) and Computer Vision and Pattern Recognition (168 citations). Fabian Both has collaborated with scholars based in Germany, Australia and Hong Kong. Frequent co-authors include Achim Rettinger, Marc T. P. Adam, Beat Peter Müller-Stich, Klaus Hermann Maier-Hein, Christof Weinhardt, Manuel Wiesenfarth, Sebastian Bodenstedt, Fabian Isensee, Hannes Kenngott and Stefanie Speidel. Their work appears in journals such as IEEE Transactions on Medical Imaging, International Journal of Computer Assisted Radiology and Surgery, Economics Letters and Lecture notes in computer science.
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.