Karsten Wendt
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Digital Imaging for Blood Diseases
Papers in
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- AI in cancer detection 4
- Neural Networks and Applications 3
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- Digital Imaging for Blood Diseases 5
- Co-authors
- Martin Bornhäuser (9 shared papers)Jan Moritz Middeke (9 shared papers)Jan‐Niklas Eckardt (9 shared papers)Frank Kroschinsky (5 shared papers)Johannes Schetelig (2 shared papers)Michael Krämer (2 shared papers)Christian Thiede (3 shared papers)Katja Sockel (5 shared papers)
- Journals
- Blood (2 papers)Blood Advances (1 paper)Journal of Personalized Medicine (1 paper)Frontiers in Oncology (1 paper)Cancers (1 paper)
- Partner nations
- GermanySwitzerlandUnited States
In The Last Decade
Karsten Wendt
15 papers receiving 288 citations
Peers
Comparison fields: 5 of 65
- Health Informatics 28
- Computer Vision and Pattern Recognition 96
- Hematology 37
- Biophysics 20
- Radiology, Nuclear Medicine and Imaging 61
Countries citing papers authored by Karsten Wendt
This map shows the geographic impact of Karsten Wendt'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 Karsten Wendt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karsten Wendt more than expected).
Fields of papers citing papers by Karsten Wendt
This network shows the impact of papers produced by Karsten Wendt. 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 Karsten Wendt. The network helps show where Karsten Wendt may publish in the future.
Co-authors
The 25 scholars most cited alongside Karsten Wendt, 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 | 2021 | 68 | |
| 2 | 2020 | 58 | |
| 3 | 2021 | 54 | |
| 4 | 2022 | 45 | |
| 5 | 2022 | 27 | |
| 6 | 2022 | 10 | |
| 7 | A graph theoretical approach for a multistep mapping software for the FACETS project | 2008 | 7 |
| 8 | 2007 | 7 | |
| 9 | 2010 | 7 | |
| 10 | 2025 | 4 | |
| 11 | 2022 | 2 | |
| 12 | Abbildung komplexer, pulsierender, neuronaler Netzwerke auf spezielle Neuronale VLSI Hardware | 2007 | 2 |
| 13 | 2024 | 1 | |
| 14 | 2024 | 1 | |
| 15 | 2010 | 1 | |
| 16 | 2025 | 0 | |
| 17 | 2025 | 0 |
About Karsten Wendt
Karsten Wendt is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Hematology, Electrical and Electronic Engineering and Computer Networks and Communications, having authored 17 papers that have together received 294 indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (5 papers), AI in cancer detection (4 papers), Neural Networks and Applications (3 papers), Advanced Memory and Neural Computing (3 papers), Acute Myeloid Leukemia Research (2 papers), Cancer Genomics and Diagnostics (2 papers), Cell Image Analysis Techniques (2 papers) and Hematological disorders and diagnostics (2 papers). The work is most often cited by research in Health Informatics (28 citations), Computer Vision and Pattern Recognition (96 citations), Hematology (37 citations), Biophysics (20 citations) and Radiology, Nuclear Medicine and Imaging (61 citations). Karsten Wendt has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Martin Bornhäuser, Jan Moritz Middeke, Jan‐Niklas Eckardt, Frank Kroschinsky, Johannes Schetelig, Michael Krämer, Christian Thiede, Katja Sockel, Christoph Röllig and Ulrich S. Schuler. Their work appears in journals such as Blood, Blood Advances, Journal of Personalized Medicine, Frontiers in Oncology and Cancers.
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.