Rushabh Doshi
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- Radiology practices and education
Papers in
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- Primary Care and Health Outcomes 2
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- Artificial Intelligence in Healthcare and Education 6
- Co-authors
- Kanhai Amin (9 shared papers)P.K. Khosla (6 shared papers)Howard P. Forman (4 shared papers)Simar S. Bajaj (3 shared papers)Reem Z. Sharaiha (4 shared papers)Michel Kahaleh (4 shared papers)Amy Tyberg (3 shared papers)Amit P. Desai (2 shared papers)
- Journals
- Gastrointestinal Endoscopy (3 papers)The Yale Journal of Biology and Medicine (3 papers)Radiology (2 papers)Healthcare (1 paper)JAMA Cardiology (1 paper)
- Partner nations
- United StatesBulgariaBangladesh
In The Last Decade
Rushabh Doshi
18 papers receiving 374 citations
Peers
Comparison fields: 5 of 69
- Health Informatics 139
- Radiology, Nuclear Medicine and Imaging 115
- Oncology 109
- Family Practice 8
- Surgery 146
Countries citing papers authored by Rushabh Doshi
This map shows the geographic impact of Rushabh Doshi'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 Rushabh Doshi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rushabh Doshi more than expected).
Fields of papers citing papers by Rushabh Doshi
This network shows the impact of papers produced by Rushabh Doshi. 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 Rushabh Doshi. The network helps show where Rushabh Doshi may publish in the future.
Co-authors
The 25 scholars most cited alongside Rushabh Doshi, 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 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 129 | |
| 2 | 2023 | 60 | |
| 3 | 2024 | 56 | |
| 4 | 2023 | 42 | |
| 5 | 2023 | 31 | |
| 6 | 2024 | 19 | |
| 7 | 2023 | 11 | |
| 8 | 2016 | 8 | |
| 9 | 2020 | 7 | |
| 10 | 2016 | 4 | |
| 11 | 2016 | 3 | |
| 12 | 2025 | 2 | |
| 13 | 2025 | 2 | |
| 14 | 2024 | 2 | |
| 15 | 2025 | 1 | |
| 16 | 2016 | 1 | |
| 17 | 1991 | 1 | |
| 18 | 2024 | 1 | |
| 19 | 2025 | 0 | |
| 20 | 2025 | 0 |
About Rushabh Doshi
Rushabh Doshi is a scholar working on General Health Professions, Health Informatics, Radiology, Nuclear Medicine and Imaging, Surgery and Oncology, having authored 21 papers that have together received 380 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (6 papers), Radiology practices and education (3 papers), Pancreatitis Pathology and Treatment (2 papers), Healthcare Policy and Management (2 papers), Pancreatic and Hepatic Oncology Research (2 papers), Primary Care and Health Outcomes (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Topic Modeling (2 papers). The work is most often cited by research in Health Informatics (139 citations), Radiology, Nuclear Medicine and Imaging (115 citations), Oncology (109 citations), Family Practice (8 citations) and Surgery (146 citations). Rushabh Doshi has collaborated with scholars based in United States, Bulgaria and Bangladesh. Frequent co-authors include Kanhai Amin, P.K. Khosla, Howard P. Forman, Simar S. Bajaj, Reem Z. Sharaiha, Michel Kahaleh, Amy Tyberg, Amit P. Desai, Kunal Karia and Moamen Gabr. Their work appears in journals such as Gastrointestinal Endoscopy, The Yale Journal of Biology and Medicine, Radiology, Healthcare and JAMA Cardiology.
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.