Frauke Wilm
Impact in
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- Artificial Intelligence in Healthcare and Education
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- Cell Image Analysis Techniques
Papers in
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- AI in cancer detection 10
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- Digital Imaging for Blood Diseases 3
- Medical Image Segmentation Techniques 2
- Generative Adversarial Networks and Image Synthesis 2
- Advanced Image and Video Retrieval Techniques 2
- Co-authors
- Katharina Breininger (12 shared papers)Marc Aubreville (10 shared papers)Christof Bertram (8 shared papers)Robert Klopfleisch (8 shared papers)Andreas Maier (9 shared papers)Christian Marzahl (6 shared papers)Taryn Donovan (2 shared papers)Mitko Veta (2 shared papers)
- Journals
- Scientific Data (3 papers)Journal of Pathology Informatics (2 papers)Veterinary Pathology (1 paper)The Journal of Pathology Clinical Research (1 paper)Biomedical Signal Processing and Control (1 paper)
- Partner nations
- GermanyAustriaNetherlands
In The Last Decade
Frauke Wilm
13 papers receiving 79 citations
Peers
Comparison fields: 5 of 31
- Health Informatics 6
- Biophysics 11
- Artificial Intelligence 51
- Radiology, Nuclear Medicine and Imaging 25
- Computer Vision and Pattern Recognition 24
Countries citing papers authored by Frauke Wilm
This map shows the geographic impact of Frauke Wilm'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 Frauke Wilm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frauke Wilm more than expected).
Fields of papers citing papers by Frauke Wilm
This network shows the impact of papers produced by Frauke Wilm. 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 Frauke Wilm. The network helps show where Frauke Wilm may publish in the future.
Co-authors
The 25 scholars most cited alongside Frauke Wilm, 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 | 2023 | 20 | |
| 2 | 2023 | 18 | |
| 3 | 2022 | 14 | |
| 4 | 2022 | 5 | |
| 5 | 2023 | 4 | |
| 6 | Robust Quad-Tree based Registration on Whole Slide Images | 2021 | 4 |
| 7 | 2022 | 4 | |
| 8 | 2018 | 3 | |
| 9 | 2024 | 3 | |
| 10 | 2023 | 3 | |
| 11 | 2025 | 2 | |
| 12 | 2023 | 2 | |
| 13 | 2021 | 1 | |
| 14 | 2025 | 0 |
About Frauke Wilm
Frauke Wilm is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Oncology, Radiology, Nuclear Medicine and Imaging and Biophysics, having authored 14 papers that have together received 83 indexed citations. Recurring topics across this work include AI in cancer detection (10 papers), Digital Imaging for Blood Diseases (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Cancer Genomics and Diagnostics (2 papers), Cutaneous Melanoma Detection and Management (2 papers), Medical Image Segmentation Techniques (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers) and Advanced Image and Video Retrieval Techniques (2 papers). The work is most often cited by research in Health Informatics (6 citations), Biophysics (11 citations), Artificial Intelligence (51 citations), Radiology, Nuclear Medicine and Imaging (25 citations) and Computer Vision and Pattern Recognition (24 citations). Frauke Wilm has collaborated with scholars based in Germany, Austria and Netherlands. Frequent co-authors include Katharina Breininger, Marc Aubreville, Christof Bertram, Robert Klopfleisch, Andreas Maier, Christian Marzahl, Taryn Donovan, Mitko Veta, Samir Jabari and P. J. van Diest. Their work appears in journals such as Scientific Data, Journal of Pathology Informatics, Veterinary Pathology, The Journal of Pathology Clinical Research and Biomedical Signal Processing and Control.
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.