Gisela Schwab
- Oncology top 5%
- Pancreatic and Hepatic Oncology Research 6
- HER2/EGFR in Cancer Research 3
- Genetics top 10%
- Chronic Lymphocytic Leukemia Research 3
- Hepatology top 10%
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- Renal cell carcinoma treatment 7
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- Renal and related cancers 4
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- Statistical Methods in Clinical Trials 4
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- Economic and Financial Impacts of Cancer 3
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- Cancer Genomics and Diagnostics 3
- Co-authors
- Lorin RoskosRafael G. AmadoRobert A. FiglinXiaodong YangAya JakobovitsEric K. RowinskyRonald M. BukowskiJohn A. Thompson
- Journals
- Journal of Clinical Oncology (6 papers)European Journal of Cancer (2 papers)Clinical Trials (2 papers)
- Partner nations
- United StatesUnited KingdomFrance
In The Last Decade
Gisela Schwab
23 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 98
- Oncology 644
- Radiology, Nuclear Medicine and Imaging 334
- Genetics 135
- Hepatology 100
- Pulmonary and Respiratory Medicine 352
Countries citing papers authored by Gisela Schwab
This map shows the geographic impact of Gisela Schwab'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 Gisela Schwab with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gisela Schwab more than expected).
Fields of papers citing papers by Gisela Schwab
This network shows the impact of papers produced by Gisela Schwab. 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 Gisela Schwab. The network helps show where Gisela Schwab may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gisela Schwab, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 12 | |
| 2 | 2021 | 15 | |
| 3 | 2021 | 4 | |
| 4 | 2021 | 6 | |
| 5 | 2020 | 3 | |
| 6 | 2019 | 43 | |
| 7 | 2018 | 8 | |
| 8 | 2018 | 4 | |
| 9 | 2018 | 69 | |
| 10 | 2017 | 42 | |
| 11 | 2016 | 55 | |
| 12 | 2016 | 2 | |
| 13 | 2008 | 95 | |
| 14 | 2007 | 153 | |
| 15 | 2006 | 71 | |
| 16 | 2004 | 177 | |
| 17 | 2004 | 73 | |
| 18 | 2004 | 243 | |
| 19 | 1997 | 3 | |
| 20 | 1987 | 50 |
About Gisela Schwab
Gisela Schwab is a scholar working on Statistics and Probability, Oncology and Genetics, having authored 23 papers that have together received 1.3k indexed citations. Recurring topics across this work include Renal cell carcinoma treatment (7 papers), Pancreatic and Hepatic Oncology Research (6 papers), Renal and related cancers (4 papers), Statistical Methods in Clinical Trials (4 papers), Chronic Lymphocytic Leukemia Research (3 papers), Economic and Financial Impacts of Cancer (3 papers), HER2/EGFR in Cancer Research (3 papers) and Cancer Genomics and Diagnostics (3 papers). The work is most often cited by research in Oncology (644 citations), Radiology, Nuclear Medicine and Imaging (334 citations) and Genetics (135 citations). Gisela Schwab has collaborated with scholars based in United States, United Kingdom and France. Frequent co-authors include Lorin Roskos, Rafael G. Amado, Robert A. Figlin, Xiaodong Yang, Aya Jakobovits, Eric K. Rowinsky, Ronald M. Bukowski, John A. Thompson, Kenneth A. Foon and Garry Schwartz. Their work appears in journals such as Journal of Clinical Oncology, European Journal of Cancer, Clinical Trials, JAMA Oncology and International Journal of Radiation Oncology*Biology*Physics.
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.