Arjun Sharma
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
Papers in ⓘ
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- COVID-19 diagnosis using AI 4
- Radiomics and Machine Learning in Medical Imaging 4
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- Complement system in diseases 3
- Immune Response and Inflammation 2
- Co-authors
- Markus Bosmann (9 shared papers)Marc Kohli (1 shared paper)Stephen Hobbs (1 shared paper)Kevin Croce (1 shared paper)Luciano M. Prevedello (1 shared paper)George Shih (1 shared paper)Safwan S. Halabi (1 shared paper)David R. Greaves (1 shared paper)
- Journals
- Journal of Digital Imaging (2 papers)Frontiers in Immunology (2 papers)Radiology Artificial Intelligence (1 paper)Blood (1 paper)Nature Communications (1 paper)
- Partner nations
- United StatesGermanyIndia
In The Last Decade
Arjun Sharma
24 papers receiving 693 citations
Peers
Comparison fields: 5 of 123
- Health Informatics 49
- Radiology, Nuclear Medicine and Imaging 187
- Immunology 141
- Artificial Intelligence 131
- Genetics 42
Countries citing papers authored by Arjun Sharma
This map shows the geographic impact of Arjun Sharma'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 Arjun Sharma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arjun Sharma more than expected).
Fields of papers citing papers by Arjun Sharma
This network shows the impact of papers produced by Arjun Sharma. 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 Arjun Sharma. The network helps show where Arjun Sharma may publish in the future.
Co-authors
The 25 scholars most cited alongside Arjun Sharma, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 181 | |
| 2 | 2008 | 105 | |
| 3 | 2016 | 82 | |
| 4 | 2020 | 74 | |
| 5 | 2021 | 35 | |
| 6 | 2011 | 33 | |
| 7 | 2019 | 29 | |
| 8 | 2015 | 25 | |
| 9 | 2021 | 24 | |
| 10 | 2019 | 23 | |
| 11 | 2021 | 20 | |
| 12 | 2020 | 10 | |
| 13 | 2022 | 9 | |
| 14 | 2020 | 9 | |
| 15 | 2018 | 8 | |
| 16 | LIVELINET: A Multimodal Deep Recurrent Neural Network to Predict Liveliness in Educational Videos. | 2016 | 7 |
| 17 | 2017 | 7 | |
| 18 | 2015 | 5 | |
| 19 | 2024 | 4 | |
| 20 | 2022 | 4 |
About Arjun Sharma
Arjun Sharma is a scholar working on Radiology, Nuclear Medicine and Imaging, Immunology, Molecular Biology, Infectious Diseases and Artificial Intelligence, having authored 28 papers that have together received 708 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Complement system in diseases (3 papers), Digital Radiography and Breast Imaging (2 papers), Coagulation, Bradykinin, Polyphosphates, and Angioedema (2 papers), Immune Response and Inflammation (2 papers), Parasites and Host Interactions (2 papers) and RNA modifications and cancer (2 papers). The work is most often cited by research in Health Informatics (49 citations), Radiology, Nuclear Medicine and Imaging (187 citations), Immunology (141 citations), Artificial Intelligence (131 citations) and Genetics (42 citations). Arjun Sharma has collaborated with scholars based in United States, Germany and India. Frequent co-authors include Markus Bosmann, Marc Kohli, Stephen Hobbs, Kevin Croce, Luciano M. Prevedello, George Shih, Safwan S. Halabi, David R. Greaves, Can Shi and Carol C. Wu. Their work appears in journals such as Journal of Digital Imaging, Frontiers in Immunology, Radiology Artificial Intelligence, Blood and Nature Communications.
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.