Yu Shen
Impact in
- Statistics and Probability top 0.5%
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Cancer Research top 0.5%
- Breast Cancer Treatment Studies
Papers in
-
- Breast Cancer Treatment Studies 46
- Oncology 58
- Global Cancer Incidence and Screening 18
- Co-authors
- Jing Qin (19 shared papers)Sijin Wen (14 shared papers)Randall E. Millikan (10 shared papers)Arlene O. Siefker‐Radtke (10 shared papers)Jing Ning (32 shared papers)Colin P. Dinney (10 shared papers)Isabelle Bedrosian (36 shared papers)Elihu H. Estey (14 shared papers)
- Journals
- Biometrics (16 papers)Cancer (16 papers)Journal of Clinical Oncology (14 papers)Statistics in Medicine (11 papers)International Journal of Radiation Oncology*Biology*Physics (10 papers)
- Partner nations
- United StatesChinaSpain
In The Last Decade
Yu Shen
276 papers receiving 8.8k citations
Peers
Comparison fields: 5 of 160
- Statistics and Probability 954
- Cancer Research 1.5k
- Oncology 2.2k
- Hematology 665
- Urology 228
Countries citing papers authored by Yu Shen
This map shows the geographic impact of Yu Shen'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 Yu Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu Shen more than expected).
Fields of papers citing papers by Yu Shen
This network shows the impact of papers produced by Yu Shen. 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 Yu Shen. The network helps show where Yu Shen may publish in the future.
Co-authors
The 25 scholars most cited alongside Yu Shen, 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 288 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 402 | |
| 2 | 2019 | 245 | |
| 3 | 2003 | 226 | |
| 4 | 2010 | 214 | |
| 5 | 2015 | 213 | |
| 6 | 2006 | 199 | |
| 7 | 2005 | 192 | |
| 8 | 2004 | 170 | |
| 9 | 2013 | 149 | |
| 10 | 2012 | 124 | |
| 11 | 1999 | 124 | |
| 12 | 2007 | 122 | |
| 13 | 2011 | 120 | |
| 14 | Elevated soluble Fas (sFas) levels in nonhematopoietic human malignancy. | 1996 | 119 |
| 15 | 2014 | 111 | |
| 16 | 2004 | 107 | |
| 17 | 2001 | 105 | |
| 18 | 2001 | 103 | |
| 19 | 2015 | 99 | |
| 20 | 2009 | 97 |
About Yu Shen
Yu Shen is a scholar working on Cancer Research, Oncology, Statistics and Probability, Molecular Biology and Pulmonary and Respiratory Medicine, having authored 288 papers that have together received 9.0k indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (46 papers), Statistical Methods and Inference (42 papers), Statistical Methods and Bayesian Inference (29 papers), Statistical Methods in Clinical Trials (26 papers), Global Cancer Incidence and Screening (18 papers), Multiple Myeloma Research and Treatments (14 papers), Advanced Causal Inference Techniques (14 papers) and Protein Degradation and Inhibitors (14 papers). The work is most often cited by research in Statistics and Probability (954 citations), Cancer Research (1.5k citations), Oncology (2.2k citations), Hematology (665 citations) and Urology (228 citations). Yu Shen has collaborated with scholars based in United States, China and Spain. Frequent co-authors include Jing Qin, Sijin Wen, Randall E. Millikan, Arlene O. Siefker‐Radtke, Jing Ning, Colin P. Dinney, Isabelle Bedrosian, Elihu H. Estey, Stephen W. Fesik and Louis L. Pisters. Their work appears in journals such as Biometrics, Cancer, Journal of Clinical Oncology, Statistics in Medicine 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.