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
-
- AI in cancer detection 4
- Neural Networks and Applications 3
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- Digital Imaging for Blood Diseases 5
- Co-authors
- Jan Moritz Middeke (9 shared papers)Jan‐Niklas Eckardt (9 shared papers)Martin Bornhäuser (9 shared papers)Johannes Schetelig (2 shared papers)Christoph Röllig (4 shared papers)Christian Thiede (3 shared papers)Frank Kroschinsky (5 shared papers)Katja Sockel (5 shared papers)
- Journals
- Blood (2 papers)Cancers (1 paper)Frontiers in Oncology (1 paper)Journal of Personalized Medicine (1 paper)npj Digital Medicine (1 paper)
- Partner nations
- GermanySwitzerlandUnited States
In The Last Decade
Karsten Wendt
15 papers receiving 260 citations
Peers
Comparison fields: 5 of 67
- Health Informatics 29
- Computer Vision and Pattern Recognition 99
- Biophysics 20
- Hematology 36
- Artificial Intelligence 96
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 | 60 | |
| 2 | 2020 | 53 | |
| 3 | 2021 | 48 | |
| 4 | 2022 | 41 | |
| 5 | 2022 | 26 | |
| 6 | 2022 | 8 | |
| 7 | A graph theoretical approach for a multistep mapping software for the FACETS project | 2008 | 7 |
| 8 | 2007 | 7 | |
| 9 | 2010 | 7 | |
| 10 | 2025 | 3 | |
| 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 |
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 16 papers that have together received 267 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), Acute Myeloid Leukemia Research (3 papers), Advanced Memory and Neural Computing (3 papers), Cell Image Analysis Techniques (2 papers), Hematological disorders and diagnostics (2 papers) and Cancer Genomics and Diagnostics (2 papers). The work is most often cited by research in Health Informatics (29 citations), Computer Vision and Pattern Recognition (99 citations), Biophysics (20 citations), Hematology (36 citations) and Artificial Intelligence (96 citations). Karsten Wendt has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Jan Moritz Middeke, Jan‐Niklas Eckardt, Martin Bornhäuser, Johannes Schetelig, Christoph Röllig, Christian Thiede, Frank Kroschinsky, Katja Sockel, Michael Krämer and Ulrich S. Schuler. Their work appears in journals such as Blood, Cancers, Frontiers in Oncology, Journal of Personalized Medicine and npj Digital Medicine.
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.