Wee Boon Tan

1.4k citations
33 papers · 526 indexed · h-index 13

Impact in

Papers in

Wee Boon Tan

32 papers receiving 518 citations

Peers

Wee Boon Tan
Comparison fields: 5 of 94
  • Endocrinology, Diabetes and Metabolism 174
  • Surgery 190
  • Genetics 99
  • Endocrinology 15
  • Health Information Management 13
Replace Aya Kitamura with:
Aya Kitamura Japan
Alexandre S. Stephens Australia
Tahnee Bridson Australia
Helen M. Shields United States
B. Denise Raynor United States
Jonathan Wild United Kingdom
Kon‐Taik Khaw United States
Christopher B. White United States
Michelle Jacobson Canada
Wee Boon Tan relative to Aya Kitamura Japan Aya Kitamura's profile →
Citations per field
00.5×6.5×
Aya Kitamura · 1×
Citations per year

Countries citing papers authored by Wee Boon Tan

Since Specialization
Citations

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

Fields of papers citing papers by Wee Boon Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20260
2 20254
3 20243
4 20248
5 20234
6 20229
7 202210
8 202120
9 20214
10 202012
11 20209
12 201712
13 201755
14 201614
15 201529
16 201514
17 201510
18 201523
19 20122
20
Feasibility and safety of day surgery laparoscopic cholecystectomy in a university hospital using a standard clinical pathway.
200826

About Wee Boon Tan

Wee Boon Tan is a scholar working on Endocrinology, Endocrinology, Diabetes and Metabolism, Applied Psychology, Genetics and Emergency Medicine, having authored 33 papers that have together received 526 indexed citations. Recurring topics across this work include Bacterial Genetics and Biotechnology (6 papers), Thyroid Cancer Diagnosis and Treatment (6 papers), Diabetes Management and Research (4 papers), Escherichia coli research studies (4 papers), Chronic Disease Management Strategies (3 papers), Diabetes Management and Education (3 papers), Thyroid and Parathyroid Surgery (3 papers) and Mobile Health and mHealth Applications (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (174 citations), Surgery (190 citations), Genetics (99 citations), Endocrinology (15 citations) and Health Information Management (13 citations). Wee Boon Tan has collaborated with scholars based in Singapore, United States and United Kingdom. Frequent co-authors include Yong Zhang, Rajeev Parameswaran, Kee Yuan Ngiam, Lian Leng Low, Min En Nga, Yu Heng Kwan, Stephen Chang, Shu‐Sin Chng, Davide Lomanto and Julian Thumboo. Their work appears in journals such as Surgical Endoscopy, Molecular Microbiology, JAMA Network Open, Thyroid and International Journal of 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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2026