Gordon S. Abrams
Impact in
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- Digital Radiography and Breast Imaging
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- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
Papers in
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- AI in cancer detection 9
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- Digital Radiography and Breast Imaging 5
- Co-authors
- David Gur (15 shared papers)Christiane M. Hakim (8 shared papers)Marie A. Ganott (7 shared papers)Jules H. Sumkin (8 shared papers)Denise M. Chough (5 shared papers)Andriy I. Bandos (5 shared papers)Margarita L. Zuley (5 shared papers)Ronald L. Perrin (1 shared paper)
- Journals
- Academic Radiology (4 papers)American Journal of Roentgenology (4 papers)Medical Physics (2 papers)Journal of Pediatric Surgery (1 paper)Radiology (1 paper)
- Partner nations
- United States
In The Last Decade
Gordon S. Abrams
17 papers receiving 730 citations
Peers
Comparison fields: 5 of 47
- Pulmonary and Respiratory Medicine 466
- Radiology, Nuclear Medicine and Imaging 279
- Artificial Intelligence 314
- Health Informatics 5
- Oncology 87
Countries citing papers authored by Gordon S. Abrams
This map shows the geographic impact of Gordon S. Abrams'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 Gordon S. Abrams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gordon S. Abrams more than expected).
Fields of papers citing papers by Gordon S. Abrams
This network shows the impact of papers produced by Gordon S. Abrams. 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 Gordon S. Abrams. The network helps show where Gordon S. Abrams may publish in the future.
Co-authors
The 25 scholars most cited alongside Gordon S. Abrams, 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 | 2009 | 283 | |
| 2 | 2008 | 115 | |
| 3 | 2006 | 59 | |
| 4 | 2009 | 45 | |
| 5 | 2014 | 44 | |
| 6 | 2007 | 36 | |
| 7 | 2005 | 32 | |
| 8 | 2019 | 26 | |
| 9 | 2004 | 24 | |
| 10 | 2021 | 21 | |
| 11 | 2006 | 15 | |
| 12 | 1997 | 12 | |
| 13 | 2006 | 12 | |
| 14 | 2008 | 11 | |
| 15 | 2007 | 8 | |
| 16 | 2007 | 7 | |
| 17 | 2005 | 1 |
About Gordon S. Abrams
Gordon S. Abrams is a scholar working on Artificial Intelligence, Pulmonary and Respiratory Medicine, Pathology and Forensic Medicine, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 17 papers that have together received 751 indexed citations. Recurring topics across this work include AI in cancer detection (9 papers), Digital Radiography and Breast Imaging (5 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Breast Lesions and Carcinomas (2 papers), Digital Imaging for Blood Diseases (1 paper), Medical Image Segmentation Techniques (1 paper), Microwave Imaging and Scattering Analysis (1 paper) and Radiology practices and education (1 paper). The work is most often cited by research in Pulmonary and Respiratory Medicine (466 citations), Radiology, Nuclear Medicine and Imaging (279 citations), Artificial Intelligence (314 citations), Health Informatics (5 citations) and Oncology (87 citations). Gordon S. Abrams has collaborated with scholars based in United States. Frequent co-authors include David Gur, Christiane M. Hakim, Marie A. Ganott, Jules H. Sumkin, Denise M. Chough, Andriy I. Bandos, Margarita L. Zuley, Ronald L. Perrin, Victor J. Catullo and Bin Zheng. Their work appears in journals such as Academic Radiology, American Journal of Roentgenology, Medical Physics, Journal of Pediatric Surgery and Radiology.
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.