Sunil Dhar

1.2k citations
58 papers · 863 · h-index 15

Impact in

Papers in

    • Cardiac Valve Diseases and Treatments 4
    • Cardiac electrophysiology and arrhythmias 3
    • Cardiac, Anesthesia and Surgical Outcomes 3
    • Blood Pressure and Hypertension Studies 3
    • Statistical Distribution Estimation and Applications 8
    • Statistical Methods in Clinical Trials 6
    • Statistical Methods and Bayesian Inference 4
    • Advanced Statistical Methods and Models 4

Sunil Dhar

51 papers receiving 837 citations

Peers

Sunil Dhar
Comparison fields: 5 of 124
  • Cardiology and Cardiovascular Medicine 241
  • Statistics and Probability 37
  • Molecular Biology 274
  • Cell Biology 65
  • Aging 6
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Citations per field
00.5×5.3×
John Fahrenbach · 1×
Citations per year

Countries citing papers authored by Sunil Dhar

Since Specialization
Citations

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

Fields of papers citing papers by Sunil Dhar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sunil Dhar, 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 Sunil Dhar Line = papers co-authored together Sunil Dhar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010120
2 201196
3 201292
4 200871
5 200959
6 201645
7 201439
8 201027
9 200926
10 201426
11 201525
12 201123
13 201818
14 201117
15 201014
16 201113
17 201012
18 201211
19 200710
20 201210

About Sunil Dhar

Sunil Dhar is a scholar working on Cardiology and Cardiovascular Medicine, Statistics and Probability, Molecular Biology, Surgery and Pulmonary and Respiratory Medicine, having authored 58 papers that have together received 863 indexed citations. Recurring topics across this work include Statistical Distribution Estimation and Applications (8 papers), Statistical Methods in Clinical Trials (6 papers), Statistical Methods and Bayesian Inference (4 papers), Cardiac Valve Diseases and Treatments (4 papers), Advanced Statistical Methods and Models (4 papers), Cardiac electrophysiology and arrhythmias (3 papers), Cardiac, Anesthesia and Surgical Outcomes (3 papers) and Blood Pressure and Hypertension Studies (3 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (241 citations), Statistics and Probability (37 citations), Molecular Biology (274 citations), Cell Biology (65 citations) and Aging (6 citations). Sunil Dhar has collaborated with scholars based in United States, India and France. Frequent co-authors include Stephen F. Vatner, Christophe Depré, Yogesh S. Shouche, Xin Zhao, Shumin Gao, David J. Morgans, Fady I. Malik, P Abarzúa, Eun H. Kim and Anna M. Barrett. Their work appears in journals such as Journal of Biopharmaceutical Statistics, American Journal of Physiology-Heart and Circulatory Physiology, Journal of Applied Probability, Journal of the American College of Cardiology and Journal of the American Statistical Association.

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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