Sean D. McGarry
- Radiology, Nuclear Medicine and Imaging top 5%
- Pulmonary and Respiratory Medicine
- Artificial Intelligence top 10%
- Genetics
- Computer Vision and Pattern Recognition
- Co-authors
- Peter S. LaVioletteAnjishnu BanerjeeJennifer ConnellyElizabeth J. CochranKenneth A. IczkowskiMark D. HohenwalterRabi YacoubWilliam A. See
- Topics
- Radiomics and Machine Learning in Medical Imaging (10 papers)MRI in cancer diagnosis (6 papers)Prostate Cancer Diagnosis and Treatment (5 papers)
- Journals
- International Journal of Radiation Oncology*Biology*PhysicsMagnetic Resonance in MedicineIEEE Transactions on Medical Imaging
- Partner nations
- United StatesBulgariaCanada
In The Last Decade
Sean D. McGarry
15 papers receiving 424 citations
Peers
Comparison fields: 5 of 60
- Radiology, Nuclear Medicine and Imaging 266
- Pulmonary and Respiratory Medicine 151
- Artificial Intelligence 109
- Genetics 78
- Computer Vision and Pattern Recognition 53
Countries citing papers authored by Sean D. McGarry
This map shows the geographic impact of Sean D. McGarry'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 Sean D. McGarry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sean D. McGarry more than expected).
Fields of papers citing papers by Sean D. McGarry
This network shows the impact of papers produced by Sean D. McGarry. 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 Sean D. McGarry. The network helps show where Sean D. McGarry may publish in the future.
Co-authorship network of co-authors of Sean D. McGarry
This figure shows the co-authorship network connecting the top 25 collaborators of Sean D. McGarry. A scholar is included among the top collaborators of Sean D. McGarry 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 Sean D. McGarry. Sean D. McGarry is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 20 | |
| 3 | 16 | |
| 4 | 4 | |
| 5 | 33 | |
| 6 | 9 | |
| 7 | 14 | |
| 8 | 1 | |
| 9 | 89 | |
| 10 | 41 | |
| 11 | 8 | |
| 12 | 43 | |
| 13 | 29 | |
| 14 | 0 | |
| 15 | 60 | |
| 16 | 56 |
About Sean D. McGarry
Sean D. McGarry is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Pulmonary and Respiratory Medicine, having authored 16 papers that have together received 426 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (10 papers), MRI in cancer diagnosis (6 papers) and Prostate Cancer Diagnosis and Treatment (5 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (266 citations), Health Informatics (13 citations) and Anesthesiology and Pain Medicine (41 citations). Sean D. McGarry has collaborated with scholars based in United States, Bulgaria and Canada. Frequent co-authors include Peter S. LaViolette, Anjishnu Banerjee, Jennifer Connelly, Elizabeth J. Cochran, Kenneth A. Iczkowski, Mark D. Hohenwalter, Rabi Yacoub, William A. See, Kuang‐Yu Jen and Brendon Lutnick. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Magnetic Resonance in Medicine and IEEE Transactions on Medical Imaging.
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.