Phillip T. Burch

49 total papers · 936 total citations
33 papers, 556 citations indexed

About

Phillip T. Burch is a scholar working on Epidemiology, Surgery and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Phillip T. Burch has authored 33 papers receiving a total of 556 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Epidemiology, 14 papers in Surgery and 13 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Phillip T. Burch's work include Congenital Heart Disease Studies (17 papers), Mechanical Circulatory Support Devices (8 papers) and Cardiac Valve Diseases and Treatments (6 papers). Phillip T. Burch is often cited by papers focused on Congenital Heart Disease Studies (17 papers), Mechanical Circulatory Support Devices (8 papers) and Cardiac Valve Diseases and Treatments (6 papers). Phillip T. Burch collaborates with scholars based in United States, Canada and Switzerland. Phillip T. Burch's co-authors include Linda M. Lambert, John A. Hawkins, Aditya K. Kaza, Richard Holubkov, William G. Cheadle, Peter C. Kouretas, Richard D. Arvey, Howard E. Miller, L. LuAnn Minich and James C. Peyton and has published in prestigious journals such as The American Journal of Cardiology, The Journal of Pediatrics and Journal of Thoracic and Cardiovascular Surgery.

In The Last Decade

Phillip T. Burch

33 papers receiving 543 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Phillip T. Burch 313 231 199 182 85 33 556
Brandon M. Wojcik 91 0.3× 250 1.1× 69 0.3× 125 0.7× 19 0.2× 36 564
Charles W. Kimbrough 138 0.4× 202 0.9× 128 0.6× 47 0.3× 117 1.4× 31 604
Jordan P. Bloom 151 0.5× 357 1.5× 201 1.0× 216 1.2× 53 0.6× 39 673
Richa Agarwal 51 0.2× 239 1.0× 121 0.6× 240 1.3× 191 2.2× 67 589
Barry J. Browne 71 0.2× 359 1.6× 155 0.8× 49 0.3× 78 0.9× 39 657
Chiara Comoglio 155 0.5× 439 1.9× 196 1.0× 250 1.4× 107 1.3× 26 642
Sarah Gelehrter 340 1.1× 307 1.3× 188 0.9× 291 1.6× 122 1.4× 34 672
Luke Kim 129 0.4× 181 0.8× 106 0.5× 212 1.2× 28 0.3× 36 529
Anna Larsson 54 0.2× 135 0.6× 84 0.4× 45 0.2× 19 0.2× 39 694
Marwa Sabe 82 0.3× 194 0.8× 83 0.4× 477 2.6× 84 1.0× 35 678

Countries citing papers authored by Phillip T. Burch

Since Specialization
Citations

This map shows the geographic impact of Phillip T. Burch'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 Phillip T. Burch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phillip T. Burch more than expected).

Fields of papers citing papers by Phillip T. Burch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Phillip T. Burch. 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 Phillip T. Burch. The network helps show where Phillip T. Burch may publish in the future.

Co-authorship network of co-authors of Phillip T. Burch

This figure shows the co-authorship network connecting the top 25 collaborators of Phillip T. Burch. A scholar is included among the top collaborators of Phillip T. Burch based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Phillip T. Burch. Phillip T. Burch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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