Arvind Shah
- Genetics top 2%
- Hemoglobinopathies and Related Disorders 21
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- Diabetes, Cardiovascular Risks, and Lipoproteins 24
- Hematology top 2%
- Surgery top 2%
- Lipoproteins and Cardiovascular Health 51
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- Cancer, Lipids, and Metabolism 22
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- Pharmaceutical Economics and Policy 15
- Health Systems, Economic Evaluations, Quality of Life 9
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- Erythrocyte Function and Pathophysiology 12
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- Kidney Stones and Urolithiasis Treatments 10
- Co-authors
- Daniel G. FosterSheryan P. EpperlyJohn W. WatsonJianxin LinAlan G. MeehanAndrew M. TershakovecSteven A. KaplanYih‐Ming Yang
- Journals
- Journal of clinical lipidology (16 papers)American Journal of Hematology (12 papers)International Journal of Clinical Practice (6 papers)
- Partner nations
- United StatesNepalUnited Kingdom
In The Last Decade
Arvind Shah
160 papers receiving 3.1k citations
Peers
Comparison fields: 5 of 152
- Genetics 544
- Endocrinology, Diabetes and Metabolism 641
- Hematology 399
- Nature and Landscape Conservation 341
- Surgery 1.1k
Countries citing papers authored by Arvind Shah
This map shows the geographic impact of Arvind Shah'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 Arvind Shah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arvind Shah more than expected).
Fields of papers citing papers by Arvind Shah
This network shows the impact of papers produced by Arvind Shah. 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 Arvind Shah. The network helps show where Arvind Shah may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Arvind Shah, 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 | 2025 | 0 | |
| 2 | 2022 | 7 | |
| 3 | 2022 | 1 | |
| 4 | Estimation of Standardized Effort in the Heterogeneous Gulf of Mexico Shrimp Fleet | 2021 | 1 |
| 5 | 2013 | 3 | |
| 6 | 2013 | 12 | |
| 7 | 2011 | 3 | |
| 8 | 2010 | 7 | |
| 9 | 2009 | 29 | |
| 10 | 2007 | 6 | |
| 11 | 2007 | 60 | |
| 12 | 2004 | 17 | |
| 13 | 2003 | 21 | |
| 14 | 2002 | 3 | |
| 15 | 2001 | 9 | |
| 16 | 1999 | 26 | |
| 17 | 1999 | 6 | |
| 18 | 1998 | 3 | |
| 19 | 1991 | 20 | |
| 20 | 1985 | 20 |
About Arvind Shah
Arvind Shah is a scholar working on Statistics and Probability, Genetics and Endocrinology, Diabetes and Metabolism, having authored 165 papers that have together received 3.3k indexed citations. Recurring topics across this work include Lipoproteins and Cardiovascular Health (51 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (24 papers), Cancer, Lipids, and Metabolism (22 papers), Hemoglobinopathies and Related Disorders (21 papers), Pharmaceutical Economics and Policy (15 papers), Erythrocyte Function and Pathophysiology (12 papers), Kidney Stones and Urolithiasis Treatments (10 papers) and Health Systems, Economic Evaluations, Quality of Life (9 papers). The work is most often cited by research in Genetics (544 citations), Endocrinology, Diabetes and Metabolism (641 citations) and Hematology (399 citations). Arvind Shah has collaborated with scholars based in United States, Nepal and United Kingdom. Frequent co-authors include Daniel G. Foster, Sheryan P. Epperly, John W. Watson, Jianxin Lin, Alan G. Meehan, Andrew M. Tershakovec, Steven A. Kaplan, Yih‐Ming Yang, Vipul N. Mankad and Elizabeth A. Manci. Their work appears in journals such as Journal of clinical lipidology, American Journal of Hematology, International Journal of Clinical Practice, The American Statistician and Lipids in Health and Disease.
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.