Simon Keek
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- MRI in cancer diagnosis
Papers in
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- Radiomics and Machine Learning in Medical Imaging 12
- Medical Imaging Techniques and Applications 3
- MRI in cancer diagnosis 1
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- Lung Cancer Diagnosis and Treatment 2
- Sarcoma Diagnosis and Treatment 1
- Co-authors
- Henry C. Woodruff (9 shared papers)Philippe Lambin (10 shared papers)Abdalla Ibrahim (5 shared papers)Sebastian Sanduleanu (5 shared papers)Turkey Refaee (3 shared papers)Ralph T. H. Leijenaar (4 shared papers)Janita E. van Timmeren (5 shared papers)Sergey Primakov (6 shared papers)
- Journals
- British Journal of Radiology (2 papers)Radiotherapy and Oncology (2 papers)Frontiers in Oncology (1 paper)Cancers (1 paper)Annals of Oncology (1 paper)
- Partner nations
- NetherlandsGermanySwitzerland
In The Last Decade
Simon Keek
12 papers receiving 510 citations
Peers
Comparison fields: 5 of 64
- Health Informatics 39
- Radiology, Nuclear Medicine and Imaging 308
- Otorhinolaryngology 18
- Pulmonary and Respiratory Medicine 84
- Artificial Intelligence 83
Countries citing papers authored by Simon Keek
This map shows the geographic impact of Simon Keek'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 Simon Keek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simon Keek more than expected).
Fields of papers citing papers by Simon Keek
This network shows the impact of papers produced by Simon Keek. 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 Simon Keek. The network helps show where Simon Keek may publish in the future.
Co-authors
The 25 scholars most cited alongside Simon Keek, 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 | 2020 | 237 | |
| 2 | 2019 | 100 | |
| 3 | 2018 | 52 | |
| 4 | 2019 | 39 | |
| 5 | 2020 | 35 | |
| 6 | 2021 | 22 | |
| 7 | 2021 | 20 | |
| 8 | 2022 | 8 | |
| 9 | 2024 | 2 | |
| 10 | 2024 | 1 | |
| 11 | 2022 | 1 | |
| 12 | 2021 | 1 |
About Simon Keek
Simon Keek is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Artificial Intelligence, Biomedical Engineering and Genetics, having authored 12 papers that have together received 518 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (12 papers), Medical Imaging Techniques and Applications (3 papers), AI in cancer detection (3 papers), Advanced X-ray and CT Imaging (2 papers), Lung Cancer Diagnosis and Treatment (2 papers), Artificial Intelligence in Healthcare (1 paper), Sarcoma Diagnosis and Treatment (1 paper) and MRI in cancer diagnosis (1 paper). The work is most often cited by research in Health Informatics (39 citations), Radiology, Nuclear Medicine and Imaging (308 citations), Otorhinolaryngology (18 citations), Pulmonary and Respiratory Medicine (84 citations) and Artificial Intelligence (83 citations). Simon Keek has collaborated with scholars based in Netherlands, Germany and Switzerland. Frequent co-authors include Henry C. Woodruff, Philippe Lambin, Abdalla Ibrahim, Sebastian Sanduleanu, Turkey Refaee, Ralph T. H. Leijenaar, Janita E. van Timmeren, Sergey Primakov, Arthur Jochems and Renée W. Y. Granzier. Their work appears in journals such as British Journal of Radiology, Radiotherapy and Oncology, Frontiers in Oncology, Cancers and Annals of 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.