Brian C. Ayers

685 citations
48 papers · 468 · h-index 11

Impact in

Papers in

    • Mechanical Circulatory Support Devices 26
    • Soft Robotics and Applications 3
    • Surgical Simulation and Training 2
    • Transplantation: Methods and Outcomes 2
    • Tissue Engineering and Regenerative Medicine 2

Brian C. Ayers

45 papers receiving 459 citations

Peers

Brian C. Ayers
Comparison fields: 5 of 42
  • Biomedical Engineering 291
  • Health Informatics 16
  • Health Information Management 24
  • Internal Medicine 8
  • Surgery 81
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Citations per year

Countries citing papers authored by Brian C. Ayers

Since Specialization
Citations

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

Fields of papers citing papers by Brian C. Ayers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian C. Ayers. 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 Brian C. Ayers. The network helps show where Brian C. Ayers may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019120
2 201942
3 202136
4 201832
5 202026
6 201717
7 202317
8 202016
9 202016
10 201912
11 202111
12 20198
13 20228
14 20207
15 20227
16 20206
17 20206
18 20246
19 20215
20 20245

About Brian C. Ayers

Brian C. Ayers is a scholar working on Biomedical Engineering, Surgery, Internal Medicine, Health Information Management and Pulmonary and Respiratory Medicine, having authored 48 papers that have together received 468 indexed citations. Recurring topics across this work include Mechanical Circulatory Support Devices (26 papers), Soft Robotics and Applications (3 papers), Opioid Use Disorder Treatment (3 papers), Venous Thromboembolism Diagnosis and Management (2 papers), Vascular Procedures and Complications (2 papers), Surgical Simulation and Training (2 papers), Transplantation: Methods and Outcomes (2 papers) and Tissue Engineering and Regenerative Medicine (2 papers). The work is most often cited by research in Biomedical Engineering (291 citations), Health Informatics (16 citations), Health Information Management (24 citations), Internal Medicine (8 citations) and Surgery (81 citations). Brian C. Ayers has collaborated with scholars based in United States, Croatia and Switzerland. Frequent co-authors include Igor Gošev, Sunil M Prasad, Katherine L. Wood, Bryan Barrus, Amber L. Melvin, Jeffrey D. Alexis, Himabindu Vidula, Arman Kilic, Tüomas Sandholm and Sabu Thomas. Their work appears in journals such as The Journal of Heart and Lung Transplantation, The Annals of Thoracic Surgery, Annals of Vascular Surgery, Interactive Cardiovascular and Thoracic Surgery and Journal of Vascular Surgery.

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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