Bryan Wilder

46 papers receiving 1.1k citations

Bryan Wilder's Hit Papers

Test sensitivity is secondary to frequency and turnaround time for COVID-19 screening 2021 · 578 citations
5780+1+3Years since publication100200300400500

Peers

Bryan Wilder
Comparison fields: 5 of 126
  • Modeling and Simulation 194
  • Infectious Diseases 471
  • Statistical and Nonlinear Physics 117
  • Health Informatics 9
  • Computer Science Applications 35
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Citations per field
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Citations per year

Countries citing papers authored by Bryan Wilder

Since Specialization
Citations

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

Fields of papers citing papers by Bryan Wilder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Test sensitivity is secondary to frequency and turnaround time for COVID-19 screening
Hit paper breakdown →
2021578
2 201989
3 202040
4 202036
5 201835
6 201826
7 201725
8 201722
9 201722
10 202022
11 201819
12 201719
13 201513
14 201811
15 201911
16 201811
17 201811
18 201811
19 20219
20 20209

About Bryan Wilder

Bryan Wilder is a scholar working on Artificial Intelligence, Sociology and Political Science, Modeling and Simulation, General Health Professions and Statistical and Nonlinear Physics, having authored 50 papers that have together received 1.1k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (10 papers), Complex Network Analysis Techniques (8 papers), Homelessness and Social Issues (7 papers), Opinion Dynamics and Social Influence (7 papers), Evolutionary Game Theory and Cooperation (5 papers), Spam and Phishing Detection (4 papers), Data-Driven Disease Surveillance (4 papers) and Evolution and Genetic Dynamics (3 papers). The work is most often cited by research in Modeling and Simulation (194 citations), Infectious Diseases (471 citations), Statistical and Nonlinear Physics (117 citations), Health Informatics (9 citations) and Computer Science Applications (35 citations). Bryan Wilder has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Milind Tambe, Michael J. Mina, James A. Hay, Soraya I. Shehata, Roy Parker, Daniel B. Larremore, Evan Lester, James M. Burke, Bistra Dilkina and Eric Rice. Their work appears in journals such as Aequationes Mathematicae, PLoS Computational Biology, Journal of the Society for Social Work and Research, International Journal of Artificial Intelligence in Education and Archives of Women s Mental Health.

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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