Jens Kleesiek
- Radiology, Nuclear Medicine and Imaging top 1%
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Neurology top 2%
- Pulmonary and Respiratory Medicine top 10%
- Co-authors
- Jan EggerMartin BendszusGregor UrbanJianning LiKlaus Maier‐HeinArmin BillerDániel SchwarzAlexander Hubert
- Topics
- Radiomics and Machine Learning in Medical Imaging (37 papers)AI in cancer detection (22 papers)Artificial Intelligence in Healthcare and Education (19 papers)
- Journals
- Nature MedicineSHILAP Revista de lepidopterologíaIEEE Transactions on Pattern Analysis and Machine Intelligence
- Partner nations
- GermanyAustriaUnited States
In The Last Decade
Jens Kleesiek
90 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 163
- Radiology, Nuclear Medicine and Imaging 994
- Artificial Intelligence 503
- Computer Vision and Pattern Recognition 501
- Neurology 436
- Pulmonary and Respiratory Medicine 385
Countries citing papers authored by Jens Kleesiek
This map shows the geographic impact of Jens Kleesiek'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 Jens Kleesiek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jens Kleesiek more than expected).
Fields of papers citing papers by Jens Kleesiek
This network shows the impact of papers produced by Jens Kleesiek. 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 Jens Kleesiek. The network helps show where Jens Kleesiek may publish in the future.
Co-authorship network of co-authors of Jens Kleesiek
This figure shows the co-authorship network connecting the top 25 collaborators of Jens Kleesiek. A scholar is included among the top collaborators of Jens Kleesiek based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jens Kleesiek. Jens Kleesiek is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 5 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 1 | |
| 11 | 3 | |
| 12 | CellViT: Vision Transformers for precise cell segmentation and classificationbreakdown → | 96 |
| 13 | 8 | |
| 14 | 6 | |
| 15 | 12 | |
| 16 | 7 | |
| 17 | 5 | |
| 18 | 32 | |
| 19 | 19 | |
| 20 | 12 |
About Jens Kleesiek
Jens Kleesiek is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 107 papers that have together received 2.3k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (37 papers), AI in cancer detection (22 papers) and Artificial Intelligence in Healthcare and Education (19 papers). The work is most often cited by research in Health Informatics (251 citations), Neurology (436 citations) and Radiology, Nuclear Medicine and Imaging (994 citations). Jens Kleesiek has collaborated with scholars based in Germany, Austria and United States. Frequent co-authors include Jan Egger, Martin Bendszus, Gregor Urban, Jianning Li, Klaus Maier‐Hein, Armin Biller, Dániel Schwarz, Alexander Hubert, Behrus Puladi and Christina Gsaxner. Their work appears in journals such as Nature Medicine, SHILAP Revista de lepidopterología and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.