Shanshan Wu

7.4k total citations · 1 hit paper
234 papers, 5.1k citations indexed

About

Shanshan Wu is a scholar working on Epidemiology, Surgery and Hepatology. According to data from OpenAlex, Shanshan Wu has authored 234 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Epidemiology, 35 papers in Surgery and 28 papers in Hepatology. Recurrent topics in Shanshan Wu's work include Liver Disease Diagnosis and Treatment (25 papers), Hepatitis B Virus Studies (16 papers) and Diabetes Treatment and Management (14 papers). Shanshan Wu is often cited by papers focused on Liver Disease Diagnosis and Treatment (25 papers), Hepatitis B Virus Studies (16 papers) and Diabetes Treatment and Management (14 papers). Shanshan Wu collaborates with scholars based in China, United States and United Kingdom. Shanshan Wu's co-authors include Siyan Zhan, Feng Sun, Zhirong Yang, Yuan Zhang, John A. Silander, Andrew M. Latimer, Alan E. Gelfand, Linong Ji, Kai Yu and Lishi Li and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Shanshan Wu

216 papers receiving 5.0k citations

Hit Papers

Rapid Detection of COVID-19 Coronavirus Using a Reverse T... 2020 2026 2022 2024 2020 100 200 300

Peers

Shanshan Wu
Comparison fields: 5 of 184
  • Epidemiology 1.1k
  • Molecular Biology 977
  • Endocrinology, Diabetes and Metabolism 834
  • Surgery 709
  • Infectious Diseases 584
Replace Gang Wang with:
Gang Wang China
Lin Xu China
Rémi Nevière France
Krzysztof Safranow Poland
Glinda S. Cooper United States
Wei Liu China
Mario Rotondi Italy
Chisato Mori Japan
Yan Zhang China
Carla Giordano Italy
Gang Wang China View profile →
Citations per field, relative to Shanshan Wu
Shanshan Wu · 1×
Citations per year, relative to Shanshan Wu
Shanshan Wu · 1×

Countries citing papers authored by Shanshan Wu

Since Specialization
Citations

This map shows the geographic impact of Shanshan Wu'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 Shanshan Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shanshan Wu more than expected).

Fields of papers citing papers by Shanshan Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shanshan Wu. 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 Shanshan Wu. The network helps show where Shanshan Wu may publish in the future.

Co-authorship network of co-authors of Shanshan Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Shanshan Wu. A scholar is included among the top collaborators of Shanshan Wu 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 Shanshan Wu. Shanshan Wu 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 5
2 5
3 1
4 1
5 1
6 3
7 1
8 2
9 3
10 1
11 7
12 5
13 20
14 7
15 1
16 17
17 7
18 38
19 1
20 72

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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