Brian Wayda

2.1k citations
32 papers · 1.2k indexed · 1 hit paper · h-index 11

Brian Wayda

25 papers receiving 1.2k citations

Hit Papers

The Use of Google Trends in Health Care Research: A Syste...6962014202620182022200400600

Peers

Brian Wayda
Comparison fields: 5 of 135
  • Transplantation 90
  • Modeling and Simulation 86
  • Health 129
  • Epidemiology 497
  • Statistics, Probability and Uncertainty 88
Replace Sara Kim with:
Sara Kim United States
Elisa F Long United States
Lauren Sinnenberg United States
Brigid Unim Italy
Isuru Ranasinghe Australia
Patricia Harrington Ireland
Ruth Davies United Kingdom
Chiara Cadeddu Italy
Alec Miners United Kingdom
Annette Rid United States
Brian Wayda relative to Sara Kim United States Sara Kim's profile →
Citations per field
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Sara Kim · 1×
Citations per year

Countries citing papers authored by Brian Wayda

Since Specialization
Citations

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

Fields of papers citing papers by Brian Wayda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
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11 202215
12 20223
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14 20212
15 20217
16 20219
17 201886
18 2016151
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The Use of Google Trends in Health Care Research: A Systematic Reviewbreakdown →
2014696
20 20147

About Brian Wayda

Brian Wayda is a scholar working on Transplantation, Surgery, Emergency Medicine, Cardiology and Cardiovascular Medicine and Hepatology, having authored 32 papers that have together received 1.2k indexed citations. Recurring topics across this work include Transplantation: Methods and Outcomes (21 papers), Renal Transplantation Outcomes and Treatments (11 papers), Mechanical Circulatory Support Devices (11 papers), Organ Transplantation Techniques and Outcomes (9 papers), Cardiac Structural Anomalies and Repair (5 papers), Cardiac Arrest and Resuscitation (4 papers), Organ Donation and Transplantation (3 papers) and Organ and Tissue Transplantation Research (3 papers). The work is most often cited by research in Transplantation (90 citations), Modeling and Simulation (86 citations), Health (129 citations), Epidemiology (497 citations) and Statistics, Probability and Uncertainty (88 citations). Brian Wayda has collaborated with scholars based in United States, Canada and Belgium. Frequent co-authors include Karthik Murugiah, Serene I. Chen, Rachel P. Dreyer, Sudhakar V. Nuti, Isuru Ranasinghe, Sisi Wang, Harlan M. Krumholz, Joseph S. Ross, Yoshifumi Naka and Hiroo Takayama. Their work appears in journals such as The Journal of Heart and Lung Transplantation, Circulation Heart Failure, JACC Heart Failure, Circulation Cardiovascular Quality and Outcomes and Clinical Transplantation.

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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