Simon Keek
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
-
- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- Medical Imaging Techniques and Applications
Papers in ⓘ
-
- Radiomics and Machine Learning in Medical Imaging 12
- Medical Imaging Techniques and Applications 5
- MRI in cancer diagnosis 2
-
- Head and Neck Cancer Studies 2
- Co-authors
- Henry C. Woodruff (9 shared papers)Philippe Lambin (10 shared papers)Sebastian Sanduleanu (5 shared papers)Abdalla Ibrahim (5 shared papers)Turkey Refaee (3 shared papers)Janita E. van Timmeren (5 shared papers)Ralph T. H. Leijenaar (4 shared papers)Arthur Jochems (2 shared papers)
- Journals
- Radiotherapy and Oncology (2 papers)British Journal of Radiology (2 papers)Cancers (1 paper)Scientific Reports (1 paper)Frontiers in Oncology (1 paper)
- Partner nations
- NetherlandsGermanySwitzerland
In The Last Decade
Simon Keek
12 papers receiving 488 citations
Hit Papers
Peers
Comparison fields: 5 of 69
- Health Informatics 49
- Radiology, Nuclear Medicine and Imaging 390
- Otorhinolaryngology 29
- Pulmonary and Respiratory Medicine 138
- Artificial Intelligence 102
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 | Radiomics: from qualitative to quantitative imaging Hit paper breakdown → | 2020 | 224 |
| 2 | 2019 | 100 | |
| 3 | 2018 | 49 | |
| 4 | 2019 | 37 | |
| 5 | 2020 | 35 | |
| 6 | 2021 | 20 | |
| 7 | 2021 | 19 | |
| 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, Otorhinolaryngology, Health Information Management, Pulmonary and Respiratory Medicine and Radiation, having authored 12 papers that have together received 497 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (12 papers), Medical Imaging Techniques and Applications (5 papers), AI in cancer detection (3 papers), Advanced X-ray and CT Imaging (2 papers), Lung Cancer Diagnosis and Treatment (2 papers), MRI in cancer diagnosis (2 papers), Sarcoma Diagnosis and Treatment (2 papers) and Head and Neck Cancer Studies (2 papers). The work is most often cited by research in Health Informatics (49 citations), Radiology, Nuclear Medicine and Imaging (390 citations), Otorhinolaryngology (29 citations), Pulmonary and Respiratory Medicine (138 citations) and Artificial Intelligence (102 citations). Simon Keek has collaborated with scholars based in Netherlands, Germany and Switzerland. Frequent co-authors include Henry C. Woodruff, Philippe Lambin, Sebastian Sanduleanu, Abdalla Ibrahim, Turkey Refaee, Janita E. van Timmeren, Ralph T. H. Leijenaar, Arthur Jochems, Sergey Primakov and Renée W. Y. Granzier. Their work appears in journals such as Radiotherapy and Oncology, British Journal of Radiology, Cancers, Scientific Reports and Frontiers in 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.