Jay Patel

24.9k citations
57 papers · 1.1k · h-index 18

Impact in

Papers in

    • Tuberculosis Research and Epidemiology 12
    • COVID-19 Clinical Research Studies 3
    • Infectious Diseases and Tuberculosis 4
    • Lipoproteins and Cardiovascular Health 3

Jay Patel

49 papers receiving 1.0k citations

Peers

Jay Patel
Comparison fields: 5 of 122
  • Endocrinology, Diabetes and Metabolism 184
  • Urology 49
  • Pharmacy 35
  • Cardiology and Cardiovascular Medicine 162
  • Epidemiology 141
Replace Arnab Pal with:
Arnab Pal India
Susan Lerner United States
Rosalinda Posadas‐Sánchez Mexico
José M. Balibrea Spain
Min‐Jeong Oh South Korea
Catherine Rolland United Kingdom
Anil Kumar India
Sara A. Farmer United States
Nafiseh Vahed Iran
Kim Nguyen South Africa
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Citations per field
00.5×8.8×
Arnab Pal · 1×
Citations per year

Countries citing papers authored by Jay Patel

Since Specialization
Citations

This map shows the geographic impact of Jay Patel'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 Jay Patel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Patel more than expected).

Fields of papers citing papers by Jay Patel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay Patel. 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 Jay Patel. The network helps show where Jay Patel may publish in the future.

Co-authors

The 25 scholars most cited alongside Jay Patel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jay Patel Line = papers co-authored together Jay Patel links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008254
2 2006188
3 200853
4 201446
5 200740
6 200835
7 200732
8 200731
9 200929
10 200726
11 200726
12 201025
13 200823
14 200623
15 200722
16 202222
17 200621
18 201618
19 200917
20 202217

About Jay Patel

Jay Patel is a scholar working on Infectious Diseases, Surgery, Cardiology and Cardiovascular Medicine, Epidemiology and Endocrinology, Diabetes and Metabolism, having authored 57 papers that have together received 1.1k indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (12 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers), Infectious Diseases and Tuberculosis (4 papers), Diet and metabolism studies (3 papers), Angiogenesis and VEGF in Cancer (3 papers), COVID-19 Clinical Research Studies (3 papers), Lipoproteins and Cardiovascular Health (3 papers) and Blood Pressure and Hypertension Studies (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (184 citations), Urology (49 citations), Pharmacy (35 citations), Cardiology and Cardiovascular Medicine (162 citations) and Epidemiology (141 citations). Jay Patel has collaborated with scholars based in United Kingdom, India and United States. Frequent co-authors include Gregory Y.H. Lip, Antonio Tello‐Montoliu, Elizabeth Hughes, Elizabeth Hughes, Dorairaj Prabhakaran, Federica Barzi, Ian D. Caterson, Scott A. Lear, Rachel Huxley and Mark Woodward. Their work appears in journals such as Journal of Internal Medicine, Journal of Human Hypertension, International Journal of Clinical Practice, European Heart Journal and BMC Primary Care.

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.

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