Wee Boon Tan
Impact in
-
- Thyroid Cancer Diagnosis and Treatment
- Diabetes Management and Research
Papers in
-
- Thyroid Cancer Diagnosis and Treatment 4
- Diabetes Management and Research 2
- Genetics 6
- Bacterial Genetics and Biotechnology 6
- Co-authors
- Yong Zhang (1 shared paper)Rajeev Parameswaran (8 shared papers)Kee Yuan Ngiam (7 shared papers)Yu Heng Kwan (5 shared papers)Shu‐Sin Chng (5 shared papers)Lian Leng Low (5 shared papers)Stephen Chang (1 shared paper)Min En Nga (3 shared papers)
- Journals
- Surgical Endoscopy (4 papers)Thyroid (2 papers)Molecular Microbiology (2 papers)JAMA Network Open (2 papers)Nature Communications (1 paper)
- Partner nations
- SingaporeUnited StatesChina
In The Last Decade
Wee Boon Tan
32 papers receiving 537 citations
Peers
Comparison fields: 5 of 80
- Endocrinology, Diabetes and Metabolism 147
- Endocrinology 15
- Surgery 116
- Genetics 78
- Molecular Medicine 11
Countries citing papers authored by Wee Boon Tan
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
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-authors
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.
All Works
Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 67 | |
| 2 | 2005 | 65 | |
| 3 | 2017 | 56 | |
| 4 | 2015 | 30 | |
| 5 | Feasibility and safety of day surgery laparoscopic cholecystectomy in a university hospital using a standard clinical pathway. | 2008 | 26 |
| 6 | 2014 | 25 | |
| 7 | 2015 | 23 | |
| 8 | 2018 | 23 | |
| 9 | 2017 | 21 | |
| 10 | 2021 | 20 | |
| 11 | 2022 | 15 | |
| 12 | 2016 | 15 | |
| 13 | 2015 | 14 | |
| 14 | 2018 | 12 | |
| 15 | 2017 | 12 | |
| 16 | 2020 | 12 | |
| 17 | 2019 | 11 | |
| 18 | 2024 | 10 | |
| 19 | 2022 | 10 | |
| 20 | 2022 | 10 |
About Wee Boon Tan
Wee Boon Tan is a scholar working on Endocrinology, Diabetes and Metabolism, Genetics, Molecular Biology, Surgery and General Health Professions, having authored 34 papers that have together received 545 indexed citations. Recurring topics across this work include Bacterial Genetics and Biotechnology (6 papers), Thyroid Cancer Diagnosis and Treatment (4 papers), Escherichia coli research studies (4 papers), Mobile Health and mHealth Applications (3 papers), Diabetes Management and Research (2 papers), Thyroid and Parathyroid Surgery (2 papers), RNA and protein synthesis mechanisms (2 papers) and Bacteriophages and microbial interactions (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (147 citations), Endocrinology (15 citations), Surgery (116 citations), Genetics (78 citations) and Molecular Medicine (11 citations). Wee Boon Tan has collaborated with scholars based in Singapore, United States and China. Frequent co-authors include Yong Zhang, Rajeev Parameswaran, Kee Yuan Ngiam, Yu Heng Kwan, Shu‐Sin Chng, Lian Leng Low, Stephen Chang, Min En Nga, Davide Lomanto and Julian Thumboo. Their work appears in journals such as Surgical Endoscopy, Thyroid, Molecular Microbiology, JAMA Network Open and Nature Communications.
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.