Steven Schalekamp
- Radiology, Nuclear Medicine and Imaging top 2%
- Health Informatics top 0.1%
- Pulmonary and Respiratory Medicine top 10%
- Infectious Diseases top 5%
- Epidemiology
- Co-authors
- Bram van GinnekenKicky G. van LeeuwenMatthieu RuttenMaarten de RooijCornelia Schaefer‐ProkopErnst T. ScholtenKeelin MurphyNico Karssemeijer
- Topics
- COVID-19 diagnosis using AI (13 papers)Radiomics and Machine Learning in Medical Imaging (11 papers)Lung Cancer Diagnosis and Treatment (10 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEClinical Infectious Diseases
- Partner nations
- NetherlandsUnited StatesGermany
In The Last Decade
Steven Schalekamp
29 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Radiology, Nuclear Medicine and Imaging 767
- Health Informatics 401
- Pulmonary and Respiratory Medicine 314
- Infectious Diseases 287
- Epidemiology 233
Countries citing papers authored by Steven Schalekamp
This map shows the geographic impact of Steven Schalekamp'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 Steven Schalekamp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steven Schalekamp more than expected).
Fields of papers citing papers by Steven Schalekamp
This network shows the impact of papers produced by Steven Schalekamp. 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 Steven Schalekamp. The network helps show where Steven Schalekamp may publish in the future.
Co-authorship network of co-authors of Steven Schalekamp
This figure shows the co-authorship network connecting the top 25 collaborators of Steven Schalekamp. A scholar is included among the top collaborators of Steven Schalekamp 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 Steven Schalekamp. Steven Schalekamp is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 3 | |
| 3 | 24 | |
| 4 | 30 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | Artificial intelligence in radiology: 100 commercially available products and their scientific evidencebreakdown → | 260 |
| 8 | 40 | |
| 9 | 29 | |
| 10 | 32 | |
| 11 | 143 | |
| 12 | 37 | |
| 13 | 57 | |
| 14 | 38 | |
| 15 | 146 | |
| 16 | 8 | |
| 17 | 61 | |
| 18 | 12 | |
| 19 | 2 | |
| 20 | 24 |
About Steven Schalekamp
Steven Schalekamp is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Pharmacy, having authored 29 papers that have together received 1.3k indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (13 papers), Radiomics and Machine Learning in Medical Imaging (11 papers) and Lung Cancer Diagnosis and Treatment (10 papers). The work is most often cited by research in Health Informatics (401 citations), Radiology, Nuclear Medicine and Imaging (767 citations) and Infectious Diseases (287 citations). Steven Schalekamp has collaborated with scholars based in Netherlands, United States and Germany. Frequent co-authors include Bram van Ginneken, Kicky G. van Leeuwen, Matthieu Rutten, Maarten de Rooij, Cornelia Schaefer‐Prokop, Ernst T. Scholten, Keelin Murphy, Nico Karssemeijer, Bart Rijnders and Judith van Paassen. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Clinical Infectious Diseases.
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.