Brian Kwan

29 papers receiving 577 citations

Peers

Brian Kwan
Comparison fields: 5 of 76
  • Experimental and Cognitive Psychology 234
  • Statistics and Probability 137
  • Cognitive Neuroscience 297
  • Music 19
  • Gender Studies 48
Replace Ilaria Santoro with:
Ilaria Santoro Italy
Andria Shimi Cyprus
Melanie Hall United Kingdom
Martin R. Vasilev United Kingdom
Daniel B. Kaye United States
Darren J. Yeo Singapore
William C. Tirre United States
Seth N. Greenberg United States
Michael Kavšek Germany
António Filipe Macedo Portugal
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Citations per field
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Ilaria Santoro · 1×
Citations per year

Countries citing papers authored by Brian Kwan

Since Specialization
Citations

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

Fields of papers citing papers by Brian Kwan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Spatial representation of pitch height: the SMARC effect
2008397
2 201422
3 201521
4 200520
5 201919
6 201818
7 201917
8 202113
9 202012
10 20198
11 20167
12 20177
13 20156
14 20136
15 20194
16 20233
17 20233
18 20242
19 20222
20 20231

About Brian Kwan

Brian Kwan is a scholar working on Public Health, Environmental and Occupational Health, Emergency Medicine, Gender Studies, General Health Professions and Pulmonary and Respiratory Medicine, having authored 29 papers that have together received 597 indexed citations. Recurring topics across this work include Diversity and Career in Medicine (7 papers), Hospital Admissions and Outcomes (7 papers), Innovations in Medical Education (7 papers), Simulation-Based Education in Healthcare (2 papers), Patient Satisfaction in Healthcare (2 papers), Global Health Workforce Issues (2 papers), Health and Medical Research Impacts (2 papers) and Neuroscience and Music Perception (2 papers). The work is most often cited by research in Experimental and Cognitive Psychology (234 citations), Statistics and Probability (137 citations), Cognitive Neuroscience (297 citations), Music (19 citations) and Gender Studies (48 citations). Brian Kwan has collaborated with scholars based in United States, United Kingdom and Italy. Frequent co-authors include Bruno L. Giordano, Elena Rusconi, Brian Butterworth, Carlo Umiltà, Steven V. Angus, Anne G. Pereira, Christopher Williams, T. Robert Vu, Frédéric Blanchard and Pierre Guihard. Their work appears in journals such as Journal of Hospital Medicine, Journal of General Internal Medicine, The American Journal of Medicine, American Journal of Health-System Pharmacy and Academic Medicine.

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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