He Sun

744 citations
33 papers · 501 · h-index 13

Impact in

Papers in

He Sun

32 papers receiving 492 citations

Peers

He Sun
Comparison fields: 5 of 90
  • Complementary and alternative medicine 62
  • Statistics and Probability 60
  • Pharmacology 58
  • Toxicology 19
  • Pharmacology 68
Replace Shiew Mei Huang with:
Shiew Mei Huang United States
Joseph P. Kitzmiller United States
R Temple United States
Jong‐Lyul Ghim South Korea
Chengxian Guo China
Sang‐Goo Shin South Korea
H. T. Schneider Germany
Adithan Chandrasekaran India
Ze Yu China
He Sun relative to Shiew Mei Huang United States Shiew Mei Huang's profile →
Citations per field
00.5×4.5×
Shiew Mei Huang · 1×
Citations per year

Countries citing papers authored by He Sun

Since Specialization
Citations

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

Fields of papers citing papers by He Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside He Sun, 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 He Sun Line = papers co-authored together He Sun links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199998
2 201463
3 200045
4 202435
5 202025
6 199824
7 202123
8 200119
9 199619
10 201219
11 201415
12 199615
13 201414
14 202110
15 20239
16 20218
17 19988
18 20217
19 20186
20 20245

About He Sun

He Sun is a scholar working on Complementary and alternative medicine, Statistics and Probability, Cardiology and Cardiovascular Medicine, Oncology and Molecular Biology, having authored 33 papers that have together received 501 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (6 papers), Traditional Chinese Medicine Analysis (5 papers), Statistical Methods and Bayesian Inference (4 papers), Nitric Oxide and Endothelin Effects (2 papers), Advanced Causal Inference Techniques (2 papers), Plant-based Medicinal Research (2 papers), Pharmaceutical studies and practices (2 papers) and Head and Neck Cancer Studies (1 paper). The work is most often cited by research in Complementary and alternative medicine (62 citations), Statistics and Probability (60 citations), Pharmacology (58 citations), Toxicology (19 citations) and Pharmacology (68 citations). He Sun has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Ene Ette, Thomas M. Ludden, Julie Perry, Zhijun Chen, Jing Wu, Jin Zhou, Emmanuel O. Fadiran, Fei-Li Zhao, Shiew‐Mei Huang and Karen M. Higgins. Their work appears in journals such as The Journal of Clinical Pharmacology, Journal of Oncology, Journal of the American Medical Informatics Association, DNA and Cell Biology and Journal of the American Geriatrics Society.

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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