T. Kiet
Impact in
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Reproductive Medicine top 10%
- Ovarian cancer diagnosis and treatment
Papers in
-
- Ovarian cancer diagnosis and treatment 9
- Surgery 4
- Intraperitoneal and Appendiceal Malignancies 2
- Co-authors
- John K. Chan (19 shared papers)Kevin Blansit (5 shared papers)Daniel S. Kapp (12 shared papers)Alexander E. Sherman (8 shared papers)C. Benjamin (1 shared paper)Micah Naimark (1 shared paper)Brian T. Feeley (1 shared paper)Gabriel Wong (1 shared paper)
- Journals
- Gynecologic Oncology (18 papers)The Oncologist (2 papers)Journal of Shoulder and Elbow Surgery (1 paper)Journal of Cachexia Sarcopenia and Muscle (1 paper)Journal of Surgical Oncology (1 paper)
- Partner nations
- United StatesVietnamAustralia
In The Last Decade
T. Kiet
22 papers receiving 617 citations
Peers
Comparison fields: 5 of 78
- Cancer Research 143
- Reproductive Medicine 76
- Obstetrics and Gynecology 63
- Surgery 211
- Oncology 62
Countries citing papers authored by T. Kiet
This map shows the geographic impact of T. Kiet'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 T. Kiet with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Kiet more than expected).
Fields of papers citing papers by T. Kiet
This network shows the impact of papers produced by T. Kiet. 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 T. Kiet. The network helps show where T. Kiet may publish in the future.
Co-authors
The 25 scholars most cited alongside T. Kiet, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 191 | |
| 2 | 2014 | 124 | |
| 3 | 2014 | 68 | |
| 4 | 2012 | 55 | |
| 5 | 2011 | 45 | |
| 6 | 2014 | 40 | |
| 7 | 2014 | 31 | |
| 8 | 2012 | 28 | |
| 9 | 2014 | 24 | |
| 10 | 2014 | 7 | |
| 11 | 2012 | 5 | |
| 12 | 2011 | 3 | |
| 13 | 2012 | 3 | |
| 14 | 2011 | 2 | |
| 15 | 2012 | 2 | |
| 16 | 2011 | 1 | |
| 17 | 2012 | 1 | |
| 18 | 2012 | 1 | |
| 19 | 2012 | 1 | |
| 20 | 2013 | 1 |
About T. Kiet
T. Kiet is a scholar working on Reproductive Medicine, Surgery, Obstetrics and Gynecology, Cancer Research and Molecular Biology, having authored 25 papers that have together received 637 indexed citations. Recurring topics across this work include Ovarian cancer diagnosis and treatment (9 papers), Endometrial and Cervical Cancer Treatments (4 papers), MicroRNA in disease regulation (3 papers), Cancer-related molecular mechanisms research (3 papers), Intraperitoneal and Appendiceal Malignancies (2 papers), Cancer Mechanisms and Therapy (2 papers), Renal cell carcinoma treatment (2 papers) and Circular RNAs in diseases (2 papers). The work is most often cited by research in Cancer Research (143 citations), Reproductive Medicine (76 citations), Obstetrics and Gynecology (63 citations), Surgery (211 citations) and Oncology (62 citations). T. Kiet has collaborated with scholars based in United States, Vietnam and Australia. Frequent co-authors include John K. Chan, Kevin Blansit, Daniel S. Kapp, Alexander E. Sherman, C. Benjamin, Micah Naimark, Brian T. Feeley, Gabriel Wong, Christine Earle and Lilly Bourguignon. Their work appears in journals such as Gynecologic Oncology, The Oncologist, Journal of Shoulder and Elbow Surgery, Journal of Cachexia Sarcopenia and Muscle and Journal of Surgical Oncology.
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.