Julius Keyl
Impact in
- Biophysics top 10%
- Cell Image Analysis Techniques
Papers in
- Oncology 5
- Cancer Immunotherapy and Biomarkers 2
- Colorectal Cancer Screening and Detection 2
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- Radiomics and Machine Learning in Medical Imaging 4
- Co-authors
- Jens Kleesiek (8 shared papers)Jens Thomas Siveke (2 shared papers)Jan Egger (4 shared papers)Fabian Hörst (3 shared papers)Constantin Seibold (2 shared papers)Lukas Heine (2 shared papers)Moritz Rempe (2 shared papers)Barbara T. Grünwald (1 shared paper)
In The Last Decade
Julius Keyl
18 papers receiving 319 citations
Julius Keyl's Hit Papers
Peers
Comparison fields: 5 of 55
- Biophysics 35
- Health Informatics 8
- Radiology, Nuclear Medicine and Imaging 64
- Artificial Intelligence 101
- Computer Vision and Pattern Recognition 58
Countries citing papers authored by Julius Keyl
This map shows the geographic impact of Julius Keyl'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 Julius Keyl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julius Keyl more than expected).
Fields of papers citing papers by Julius Keyl
This network shows the impact of papers produced by Julius Keyl. 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 Julius Keyl. The network helps show where Julius Keyl may publish in the future.
Co-authors
The 25 scholars most cited alongside Julius Keyl, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | CellViT: Vision Transformers for precise cell segmentation and classification Hit paper breakdown → | 2024 | 161 |
| 2 | 2022 | 32 | |
| 3 | 2025 | 28 | |
| 4 | 2022 | 27 | |
| 5 | 2024 | 19 | |
| 6 | 2024 | 16 | |
| 7 | 2023 | 8 | |
| 8 | 2023 | 8 | |
| 9 | 2022 | 7 | |
| 10 | 2024 | 6 | |
| 11 | 2024 | 3 | |
| 12 | 2025 | 3 | |
| 13 | 2024 | 2 | |
| 14 | 2026 | 2 | |
| 15 | 2025 | 2 | |
| 16 | 2023 | 1 | |
| 17 | 2025 | 1 | |
| 18 | 2025 | 1 | |
| 19 | 2026 | 0 | |
| 20 | 2025 | 0 |
About Julius Keyl
Julius Keyl is a scholar working on Oncology, Radiology, Nuclear Medicine and Imaging, Physiology, Artificial Intelligence and Geriatrics and Gerontology, having authored 23 papers that have together received 327 indexed citations. Recurring topics across this work include Nutrition and Health in Aging (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), AI in cancer detection (4 papers), Lung Cancer Treatments and Mutations (2 papers), Cancer Immunotherapy and Biomarkers (2 papers), Lung Cancer Diagnosis and Treatment (2 papers), Colorectal Cancer Screening and Detection (2 papers) and Digital Imaging for Blood Diseases (1 paper). The work is most often cited by research in Biophysics (35 citations), Health Informatics (8 citations), Radiology, Nuclear Medicine and Imaging (64 citations), Artificial Intelligence (101 citations) and Computer Vision and Pattern Recognition (58 citations). Julius Keyl has collaborated with scholars based in Germany, Canada and Austria. Frequent co-authors include Jens Kleesiek, Jens Thomas Siveke, Jan Egger, Fabian Hörst, Constantin Seibold, Lukas Heine, Moritz Rempe, Barbara T. Grünwald, Giulia Baldini and Selma Ugurel. Their work appears in journals such as ESMO Open, Frontiers in Endocrinology, JCO Clinical Cancer Informatics, npj Digital Medicine and Journal of Critical Care.
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.