Jan van Zelst
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 5%
- Pathology and Forensic Medicine top 10%
- Pulmonary and Respiratory Medicine
- Oncology
- Co-authors
- Ritse M. MannNico KarssemeijerBram PlatelRoel MusChristian GeppertSuzan VreemannTao TanAlbert Gubern‐Mérida
- Topics
- AI in cancer detection (17 papers)Breast Lesions and Carcinomas (16 papers)Digital Radiography and Breast Imaging (9 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingPathology and Forensic MedicineArtificial Intelligence
- Partner nations
- NetherlandsUnited StatesGermany
In The Last Decade
Jan van Zelst
21 papers receiving 709 citations
Peers
Comparison fields: 5 of 54
- Radiology, Nuclear Medicine and Imaging 473
- Artificial Intelligence 311
- Pathology and Forensic Medicine 198
- Pulmonary and Respiratory Medicine 195
- Oncology 94
Countries citing papers authored by Jan van Zelst
This map shows the geographic impact of Jan van Zelst'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 Jan van Zelst with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan van Zelst more than expected).
Fields of papers citing papers by Jan van Zelst
This network shows the impact of papers produced by Jan van Zelst. 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 Jan van Zelst. The network helps show where Jan van Zelst may publish in the future.
Co-authorship network of co-authors of Jan van Zelst
This figure shows the co-authorship network connecting the top 25 collaborators of Jan van Zelst. A scholar is included among the top collaborators of Jan van Zelst 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 Jan van Zelst. Jan van Zelst 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 | 2 | |
| 3 | 19 | |
| 4 | 64 | |
| 5 | 30 | |
| 6 | 57 | |
| 7 | 55 | |
| 8 | 8 | |
| 9 | 48 | |
| 10 | 11 | |
| 11 | 45 | |
| 12 | 9 | |
| 13 | 51 | |
| 14 | 18 | |
| 15 | 15 | |
| 16 | 14 | |
| 17 | 33 | |
| 18 | 38 | |
| 19 | 164 | |
| 20 | 22 |
About Jan van Zelst
Jan van Zelst is a scholar working on Pathology and Forensic Medicine, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 23 papers that have together received 722 indexed citations. Recurring topics across this work include AI in cancer detection (17 papers), Breast Lesions and Carcinomas (16 papers) and Digital Radiography and Breast Imaging (9 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (473 citations), Pathology and Forensic Medicine (198 citations) and Artificial Intelligence (311 citations). Jan van Zelst has collaborated with scholars based in Netherlands, United States and Germany. Frequent co-authors include Ritse M. Mann, Nico Karssemeijer, Bram Platel, Roel Mus, Christian Geppert, Suzan Vreemann, Tao Tan, Albert Gubern‐Mérida, Matthieu Rutten and Peter Bult. Their work appears in journals such as Radiology, Medical Physics and Radiographics.
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.