Deep Mehta
Impact in
- Infectious Diseases top 5%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
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- COVID-19 epidemiological studies
Papers in
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- COVID-19 Clinical Research Studies 8
-
- Meta-analysis and systematic reviews 1
- Co-authors
- Urvish K. Patel (7 shared papers)Preeti Malik (6 shared papers)Henry S. Sacks (4 shared papers)Raveena Kelkar (3 shared papers)Muhammad Akrmah (1 shared paper)Janice Lynn Gabrilove (1 shared paper)Nidhi Patel (1 shared paper)Ashish Sharma (3 shared papers)
- Journals
- Journal of Stroke and Cerebrovascular Diseases (1 paper)BMJ Evidence-Based Medicine (1 paper)Journal of Medical Virology (1 paper)Journal of Clinical Gastroenterology (1 paper)Journal of Global Health (1 paper)
- Partner nations
- United StatesIndiaAntigua and Barbuda
In The Last Decade
Deep Mehta
10 papers receiving 678 citations
Peers
Comparison fields: 5 of 65
- Infectious Diseases 533
- Modeling and Simulation 16
- Neurology 42
- Applied Microbiology and Biotechnology 6
- Internal Medicine 5
Countries citing papers authored by Deep Mehta
This map shows the geographic impact of Deep Mehta'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 Deep Mehta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deep Mehta more than expected).
Fields of papers citing papers by Deep Mehta
This network shows the impact of papers produced by Deep Mehta. 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 Deep Mehta. The network helps show where Deep Mehta may publish in the future.
Co-authors
The 25 scholars most cited alongside Deep Mehta, 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 | 2020 | 450 | |
| 2 | 2020 | 81 | |
| 3 | 2020 | 69 | |
| 4 | 2020 | 47 | |
| 5 | 2020 | 45 | |
| 6 | 2021 | 7 | |
| 7 | 2022 | 4 | |
| 8 | 2021 | 2 | |
| 9 | 2023 | 1 | |
| 10 | 2025 | 1 | |
| 11 | 2024 | 0 | |
| 12 | 2025 | 0 | |
| 13 | 2025 | 0 |
About Deep Mehta
Deep Mehta is a scholar working on Infectious Diseases, Statistics, Probability and Uncertainty, Genetics, Hepatology and Cardiology and Cardiovascular Medicine, having authored 13 papers that have together received 707 indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (8 papers), Pericarditis and Cardiac Tamponade (1 paper), Liver Diseases and Immunity (1 paper), Hemoglobinopathies and Related Disorders (1 paper), Meta-analysis and systematic reviews (1 paper), Nutrition and Health in Aging (1 paper) and Gallbladder and Bile Duct Disorders (1 paper). The work is most often cited by research in Infectious Diseases (533 citations), Modeling and Simulation (16 citations), Neurology (42 citations), Applied Microbiology and Biotechnology (6 citations) and Internal Medicine (5 citations). Deep Mehta has collaborated with scholars based in United States, India and Antigua and Barbuda. Frequent co-authors include Urvish K. Patel, Preeti Malik, Henry S. Sacks, Raveena Kelkar, Muhammad Akrmah, Janice Lynn Gabrilove, Nidhi Patel, Ashish Sharma, Faizan Ahmad Malik and Karan Patel. Their work appears in journals such as Journal of Stroke and Cerebrovascular Diseases, BMJ Evidence-Based Medicine, Journal of Medical Virology, Journal of Clinical Gastroenterology and Journal of Global Health.
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.