Jurgen Peerlings
- Radiology, Nuclear Medicine and Imaging top 0.2%
- Pulmonary and Respiratory Medicine top 2%
- Biomedical Engineering top 5%
- Oncology top 5%
- Artificial Intelligence top 2%
- Co-authors
- Philippe LambinFelix M. MottaghyJoachim E. WildbergerHenry C. WoodruffRuben T. H. M. LarueRalph T. H. LeijenaarJanita E. van TimmerenArthur Jochems
- Topics
- Radiomics and Machine Learning in Medical Imaging (5 papers)Medical Imaging Techniques and Applications (4 papers)MRI in cancer diagnosis (3 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingHealth InformaticsPulmonary and Respiratory Medicine
- Partner nations
- NetherlandsGermanyUnited Kingdom
In The Last Decade
Jurgen Peerlings
9 papers receiving 4.1k citations
Hit Papers
Peers
Comparison fields: 5 of 144
- Radiology, Nuclear Medicine and Imaging 3.6k
- Pulmonary and Respiratory Medicine 1.4k
- Biomedical Engineering 942
- Oncology 766
- Artificial Intelligence 520
Countries citing papers authored by Jurgen Peerlings
This map shows the geographic impact of Jurgen Peerlings'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 Jurgen Peerlings with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jurgen Peerlings more than expected).
Fields of papers citing papers by Jurgen Peerlings
This network shows the impact of papers produced by Jurgen Peerlings. 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 Jurgen Peerlings. The network helps show where Jurgen Peerlings may publish in the future.
Co-authorship network of co-authors of Jurgen Peerlings
This figure shows the co-authorship network connecting the top 25 collaborators of Jurgen Peerlings. A scholar is included among the top collaborators of Jurgen Peerlings 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 Jurgen Peerlings. Jurgen Peerlings is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 14 | |
| 2 | 3 | |
| 3 | Stability of radiomics features in apparent diffusion coefficient maps from a multi-centre test-retest trialbreakdown → | 221 |
| 4 | 100 | |
| 5 | 40 | |
| 6 | Radiomics: the bridge between medical imaging and personalized medicinebreakdown → | 3729 |
| 7 | 12 | |
| 8 | 34 | |
| 9 | 8 |
About Jurgen Peerlings
Jurgen Peerlings is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Information Management and Reproductive Medicine, having authored 9 papers that have together received 4.2k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (5 papers), Medical Imaging Techniques and Applications (4 papers) and MRI in cancer diagnosis (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (3.6k citations), Health Informatics (197 citations) and Pulmonary and Respiratory Medicine (1.4k citations). Jurgen Peerlings has collaborated with scholars based in Netherlands, Germany and United Kingdom. Frequent co-authors include Philippe Lambin, Felix M. Mottaghy, Joachim E. Wildberger, Henry C. Woodruff, Ruben T. H. M. Larue, Ralph T. H. Leijenaar, Janita E. van Timmeren, Arthur Jochems, Sebastian Sanduleanu and Aniek J.G. Even. Their work appears in journals such as Scientific Reports, Radiology and Nature Reviews Clinical Oncology.
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.