Cornelia M. Schaefer‐Prokop
Impact in
- Radiology, Nuclear Medicine and Imaging top 0.05%
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Medical Imaging Techniques and Applications
- Health Informatics top 0.5%
Papers in
-
- Lung Cancer Diagnosis and Treatment 66
- Digital Radiography and Breast Imaging 21
- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis 18
-
- Radiomics and Machine Learning in Medical Imaging 27
- Radiation Dose and Imaging 15
- Medical Imaging Techniques and Applications 14
- COVID-19 diagnosis using AI 13
- Co-authors
- Mathias Prokop (92 shared papers)Bram van Ginneken (44 shared papers)Alexander A. Bankier (9 shared papers)David P. Naidich (5 shared papers)Jin Mo Goo (7 shared papers)Heber MacMahon (5 shared papers)William David Travis (3 shared papers)Geoffrey D. Rubin (2 shared papers)
- Journals
- Radiology (40 papers)European Radiology (26 papers)European Journal of Radiology (10 papers)Journal of Thoracic Imaging (9 papers)American Journal of Roentgenology (6 papers)
- Partner nations
- NetherlandsAustriaGermany
In The Last Decade
Cornelia M. Schaefer‐Prokop
173 papers receiving 13.2k citations
Cornelia M. Schaefer‐Prokop's Hit Papers
Peers
Comparison fields: 5 of 175
- Radiology, Nuclear Medicine and Imaging 5.8k
- Health Informatics 311
- Pulmonary and Respiratory Medicine 6.1k
- Critical Care and Intensive Care Medicine 635
- Infectious Diseases 1.2k
Countries citing papers authored by Cornelia M. Schaefer‐Prokop
This map shows the geographic impact of Cornelia M. Schaefer‐Prokop'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 Cornelia M. Schaefer‐Prokop with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cornelia M. Schaefer‐Prokop more than expected).
Fields of papers citing papers by Cornelia M. Schaefer‐Prokop
This network shows the impact of papers produced by Cornelia M. Schaefer‐Prokop. 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 Cornelia M. Schaefer‐Prokop. The network helps show where Cornelia M. Schaefer‐Prokop may publish in the future.
Co-authors
The 25 scholars most cited alongside Cornelia M. Schaefer‐Prokop, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 184 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017 Hit paper breakdown → | 2017 | 1793 |
| 2 | FDG PET and PET/CT: EANM procedure guidelines for tumour PET imaging: version 1.0 Hit paper breakdown → | 2009 | 1079 |
| 3 | The Role of Chest Imaging in Patient Management During the COVID-19 Pandemic Hit paper breakdown → | 2020 | 1034 |
| 4 | Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge Hit paper breakdown → | 2017 | 988 |
| 5 | The Role of Chest Imaging in Patient Management during the COVID-19 Pandemic: A Multinational Consensus Statement from the Fleischner Society Hit paper breakdown → | 2020 | 799 |
| 6 | Recommendations for the Management of Subsolid Pulmonary Nodules Detected at CT: A Statement from the Fleischner Society Hit paper breakdown → | 2012 | 789 |
| 7 | CO-RADS: A Categorical CT Assessment Scheme for Patients Suspected of Having COVID-19—Definition and Evaluation Hit paper breakdown → | 2020 | 635 |
| 8 | 2017 | 268 | |
| 9 | 1997 | 249 | |
| 10 | Towards automatic pulmonary nodule management in lung cancer screening with deep learning | 2017 | 243 |
| 11 | 2011 | 240 | |
| 12 | 2006 | 227 | |
| 13 | 2013 | 213 | |
| 14 | 2020 | 171 | |
| 15 | 2009 | 171 | |
| 16 | 2015 | 156 | |
| 17 | 2009 | 154 | |
| 18 | 2006 | 153 | |
| 19 | 2003 | 152 | |
| 20 | Fleischner Society: Glossary of Terms for Thoracic Imaging Hit paper breakdown → | 2024 | 143 |
About Cornelia M. Schaefer‐Prokop
Cornelia M. Schaefer‐Prokop is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Critical Care and Intensive Care Medicine, Internal Medicine and Biomedical Engineering, having authored 184 papers that have together received 13.6k indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (66 papers), Radiomics and Machine Learning in Medical Imaging (27 papers), Digital Radiography and Breast Imaging (21 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (18 papers), Advanced X-ray and CT Imaging (17 papers), Radiation Dose and Imaging (15 papers), Medical Imaging Techniques and Applications (14 papers) and COVID-19 diagnosis using AI (13 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (5.8k citations), Health Informatics (311 citations), Pulmonary and Respiratory Medicine (6.1k citations), Critical Care and Intensive Care Medicine (635 citations) and Infectious Diseases (1.2k citations). Cornelia M. Schaefer‐Prokop has collaborated with scholars based in Netherlands, Austria and Germany. Frequent co-authors include Mathias Prokop, Bram van Ginneken, Alexander A. Bankier, David P. Naidich, Jin Mo Goo, Heber MacMahon, William David Travis, Geoffrey D. Rubin, Christian Herold and Martin Uffmann. Their work appears in journals such as Radiology, European Radiology, European Journal of Radiology, Journal of Thoracic Imaging and American Journal of Roentgenology.
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.