Kevin Tan

86 papers receiving 1.1k citations

Peers

Kevin Tan
Comparison fields: 5 of 129
  • Family Practice 47
  • Neurology 205
  • Pathology and Forensic Medicine 162
  • Oncology 223
  • Virology 31
Replace Elena S. Izmailova with:
Elena S. Izmailova United States
Peter Humburg Australia
Chaeuk Chung South Korea
Aniruddha Agarwal India
Hwa Jin Cho South Korea
Madhan Jeyaraman India
Cecilia S. Lee United States
Edward Kim United States
Paolo Boscolo‐Rizzo Italy
Lehn K. Weaver United States
Kevin Tan relative to Elena S. Izmailova United States Elena S. Izmailova's profile →
Citations per field
00.5×2.9×
Elena S. Izmailova · 1×
Citations per year

Countries citing papers authored by Kevin Tan

Since Specialization
Citations

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

Fields of papers citing papers by Kevin Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 98 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009259
2 201194
3 202070
4 201051
5 201045
6 200242
7 201332
8 201430
9 200927
10 200825
11 200425
12 202124
13 202224
14 200817
15 200715
16 201814
17 201714
18 202314
19 199513
20 200813

About Kevin Tan

Kevin Tan is a scholar working on Neurology, Pathology and Forensic Medicine, Public Health, Environmental and Occupational Health, Infectious Diseases and Epidemiology, having authored 98 papers that have together received 1.1k indexed citations. Recurring topics across this work include Peripheral Neuropathies and Disorders (19 papers), Multiple Sclerosis Research Studies (14 papers), Innovations in Medical Education (13 papers), Clinical Reasoning and Diagnostic Skills (11 papers), Autoimmune Neurological Disorders and Treatments (10 papers), Bacterial Infections and Vaccines (7 papers), Infectious Encephalopathies and Encephalitis (6 papers) and Herpesvirus Infections and Treatments (5 papers). The work is most often cited by research in Family Practice (47 citations), Neurology (205 citations), Pathology and Forensic Medicine (162 citations), Oncology (223 citations) and Virology (31 citations). Kevin Tan has collaborated with scholars based in Singapore, United States and United Kingdom. Frequent co-authors include Lyle W. Ostrow, Avindra Nath, Justin C. McArthur, Nigel CK Tan, Nagaendran Kandiah, C. C. Tchoyoson Lim, Narayanaswamy Venketasubramanian, Thirugnanam Umapathi, Yiong Huak Chan and Tianrong Yeo. Their work appears in journals such as Neurology, Journal of the Neurological Sciences, Scientific Reports, Medical Education and Journal of Clinical Apheresis.

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.

Explore authors with similar magnitude of impact