Yu Shen

17.3k total citations
292 papers, 8.8k citations indexed

About

Yu Shen is a scholar working on Oncology, Cancer Research and Statistics and Probability. According to data from OpenAlex, Yu Shen has authored 292 papers receiving a total of 8.8k indexed citations (citations by other indexed papers that have themselves been cited), including 104 papers in Oncology, 81 papers in Cancer Research and 59 papers in Statistics and Probability. Recurrent topics in Yu Shen's work include Breast Cancer Treatment Studies (58 papers), Statistical Methods and Inference (42 papers) and Global Cancer Incidence and Screening (31 papers). Yu Shen is often cited by papers focused on Breast Cancer Treatment Studies (58 papers), Statistical Methods and Inference (42 papers) and Global Cancer Incidence and Screening (31 papers). Yu Shen collaborates with scholars based in United States, China and Spain. Yu Shen's co-authors include Jing Qin, Sijin Wen, Randall E. Millikan, Arlene O. Siefker‐Radtke, Jing Ning, Colin P. Dinney, Isabelle Bedrosian, Stephen W. Fesik, Elihu H. Estey and Louis L. Pisters and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Yu Shen

277 papers receiving 8.6k citations

Peers

Yu Shen
Comparison fields: 5 of 163
  • Oncology 3.1k
  • Molecular Biology 2.4k
  • Surgery 2.0k
  • Cancer Research 1.9k
  • Pulmonary and Respiratory Medicine 1.1k
Replace Christophe Le Tourneau with:
Christophe Le Tourneau France
B. Nebiyou Bekele United States
Sin‐Ho Jung United States
Rajeshwari Sridhara United States
Matthew R. Sydes United Kingdom
Gary Longton United States
Nicholas D. James United Kingdom
Alberto Ocaña Spain
Patricia Keegan United States
Kristine Broglio United States
Christophe Le Tourneau France View profile →
Citations per field, relative to Yu Shen
Yu Shen · 1×
Citations per year, relative to Yu Shen
Yu Shen · 1×

Countries citing papers authored by Yu Shen

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Yu Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Yu Shen. A scholar is included among the top collaborators of Yu Shen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yu Shen. Yu Shen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 2
2 0
3 0
4 0
5 1
6 4
7 1
8 7
9 12
10 9
11 231
12 21
13 55
14 7
15 53
16 45
17 146
18 119
19 85
20 75

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.

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