Shuang Wang

5.0k citations
210 papers · 3.1k indexed · h-index 32

Shuang Wang

189 papers receiving 3.1k citations

Peers

Shuang Wang
Comparison fields: 5 of 194
  • Health Informatics 116
  • Artificial Intelligence 1.2k
  • Health Information Management 118
  • Cancer Research 254
  • Statistics and Probability 104
Replace Zhe He with:
Zhe He United States
Elmer V. Bernstam United States
José Luís Oliveira Portugal
Cui Tao United States
Marinka Žitnik United States
Frank Emmert‐Streib Austria
Constantin Aliferis United States
Simon Lin United States
Rae Woong Park South Korea
Fang Liu China
Shuang Wang relative to Zhe He United States Zhe He's profile →
Citations per field
00.5×1.5×2.4×
Zhe He · 1×
Citations per year

Countries citing papers authored by Shuang Wang

Since Specialization
Citations

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

Fields of papers citing papers by Shuang Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Shuang Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Shuang Wang Line = papers co-authored together Shuang Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20240
3 20246
4 20244
5 20244
6 20231
7 202325
8 20230
9 20234
10 202312
11 20212
12 202056
13
M2 macrophage infiltration into tumor islets leads to poor prognosis in non-small-cell lung cancer
20193
14 2018128
15 201838
16 201823
17 20175
18 20177
19 201640
20
An Approach to Center Selection Based on Minimal Similarity Among Texts
20080

About Shuang Wang

Shuang Wang is a scholar working on Artificial Intelligence, Toxicology and Rheumatology, having authored 210 papers that have together received 3.1k indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (36 papers), Cryptography and Data Security (18 papers), Ethics in Clinical Research (14 papers), Cancer Genomics and Diagnostics (9 papers), Respiratory viral infections research (7 papers), Quantum Information and Cryptography (7 papers), Systemic Lupus Erythematosus Research (6 papers) and Autophagy in Disease and Therapy (6 papers). The work is most often cited by research in Health Informatics (116 citations), Artificial Intelligence (1.2k citations) and Health Information Management (118 citations). Shuang Wang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Xiaoqian Jiang, Lucila Ohno‐Machado, Noman Mohammed, Wenrui Dai, Miran Kim, Samuel Cheng, Hongkai Xiong, Yuhou Xia, Yongsoo Song and Zhanglong Ji. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Angewandte Chemie International Edition.

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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