Thomas Gwise
Impact in
- Statistics and Probability top 5%
- Statistical Methods in Clinical Trials
- Hematology top 10%
- Multiple Myeloma Research and Treatments
Papers in ⓘ
-
- Statistical Methods in Clinical Trials 13
- Advanced Causal Inference Techniques 3
-
- Health Systems, Economic Evaluations, Quality of Life 6
- Co-authors
- Richard Pazdur (16 shared papers)Marc R. Theoret (11 shared papers)Rajeshwari Sridhara (8 shared papers)Paul G. Kluetz (7 shared papers)Laura L. Fernandes (8 shared papers)Vishal Bhatnagar (4 shared papers)Jonathon Vallejo (4 shared papers)Bindu Kanapuru (5 shared papers)
- Journals
- Statistics in Biopharmaceutical Research (6 papers)Journal of Clinical Oncology (5 papers)Clinical Cancer Research (2 papers)Blood Cancer Journal (2 papers)Blood (2 papers)
- Partner nations
- United StatesAustriaThailand
In The Last Decade
Thomas Gwise
21 papers receiving 312 citations
Peers
Comparison fields: 5 of 61
- Statistics and Probability 100
- Hematology 76
- Cancer Research 56
- Oncology 96
- Genetics 31
Countries citing papers authored by Thomas Gwise
This map shows the geographic impact of Thomas Gwise'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 Thomas Gwise with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Gwise more than expected).
Fields of papers citing papers by Thomas Gwise
This network shows the impact of papers produced by Thomas Gwise. 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 Thomas Gwise. The network helps show where Thomas Gwise may publish in the future.
Co-authors
The 25 scholars most cited alongside Thomas Gwise, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 97 | |
| 2 | 2022 | 32 | |
| 3 | 2018 | 28 | |
| 4 | 2021 | 20 | |
| 5 | 2020 | 16 | |
| 6 | 2021 | 16 | |
| 7 | 2023 | 15 | |
| 8 | 2008 | 11 | |
| 9 | 2021 | 11 | |
| 10 | 2013 | 9 | |
| 11 | 2022 | 9 | |
| 12 | 2021 | 9 | |
| 13 | 2016 | 8 | |
| 14 | 2021 | 8 | |
| 15 | 2021 | 7 | |
| 16 | 2023 | 6 | |
| 17 | 2020 | 5 | |
| 18 | 2010 | 5 | |
| 19 | 2021 | 2 | |
| 20 | 2021 | 1 |
About Thomas Gwise
Thomas Gwise is a scholar working on Statistics and Probability, Economics and Econometrics, Cancer Research, Oncology and Hematology, having authored 24 papers that have together received 316 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (13 papers), Cancer Genomics and Diagnostics (7 papers), Health Systems, Economic Evaluations, Quality of Life (6 papers), Multiple Myeloma Research and Treatments (4 papers), Colorectal Cancer Treatments and Studies (3 papers), Advanced Causal Inference Techniques (3 papers), Cancer Treatment and Pharmacology (2 papers) and Acute Myeloid Leukemia Research (2 papers). The work is most often cited by research in Statistics and Probability (100 citations), Hematology (76 citations), Cancer Research (56 citations), Oncology (96 citations) and Genetics (31 citations). Thomas Gwise has collaborated with scholars based in United States, Austria and Thailand. Frequent co-authors include Richard Pazdur, Marc R. Theoret, Rajeshwari Sridhara, Paul G. Kluetz, Laura L. Fernandes, Vishal Bhatnagar, Jonathon Vallejo, Bindu Kanapuru, Laleh Amiri‐Kordestani and Shenghui Tang. Their work appears in journals such as Statistics in Biopharmaceutical Research, Journal of Clinical Oncology, Clinical Cancer Research, Blood Cancer Journal and Blood.
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.