Weiyi Sun

853 total citations
18 papers, 561 citations indexed

About

Weiyi Sun is a scholar working on Molecular Biology, Artificial Intelligence and Dermatology. According to data from OpenAlex, Weiyi Sun has authored 18 papers receiving a total of 561 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 8 papers in Artificial Intelligence and 5 papers in Dermatology. Recurrent topics in Weiyi Sun's work include Topic Modeling (7 papers), Biomedical Text Mining and Ontologies (6 papers) and Facial Rejuvenation and Surgery Techniques (5 papers). Weiyi Sun is often cited by papers focused on Topic Modeling (7 papers), Biomedical Text Mining and Ontologies (6 papers) and Facial Rejuvenation and Surgery Techniques (5 papers). Weiyi Sun collaborates with scholars based in China and United States. Weiyi Sun's co-authors include Anna Rumshisky, Özlem Uzuner, Tao Song, Haidong Li, Di Wu, Yongqian Wang, Li J, Dingrong Zhong, Wei Sun and Jian Sun and has published in prestigious journals such as PLoS ONE, Journal of the American Medical Informatics Association and Journal of Biomedical Informatics.

In The Last Decade

Weiyi Sun

18 papers receiving 529 citations

Peers

Weiyi Sun
Comparison fields: 5 of 71
  • Artificial Intelligence 438
  • Molecular Biology 373
  • Dermatology 42
  • Health Information Management 35
  • Surgery 23
Replace Tomasz Adamusiak with:
Tomasz Adamusiak United States
Jingming Liu China
Tian Kang United States
John Sharko United States
Michal Ozery-Flato Israel
Grant L. Hom United States
Panagiotis Papachristou Sweden
Zhiyong Lu United States
Christian Thies Germany
Kevin Faust Canada
Tomasz Adamusiak United States View profile →
Citations per field, relative to Weiyi Sun
Weiyi Sun · 1×
Citations per year, relative to Weiyi Sun
Weiyi Sun · 1×

Countries citing papers authored by Weiyi Sun

Since Specialization
Citations

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

Fields of papers citing papers by Weiyi Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Weiyi Sun

This figure shows the co-authorship network connecting the top 25 collaborators of Weiyi Sun. A scholar is included among the top collaborators of Weiyi Sun 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 Weiyi Sun. Weiyi Sun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
# Work Indexed citations
1 3
2 1
3 1
4 3
5 7
6 40
7 5
8
A Hybrid Normalization Method for Medical Concepts in Clinical Narrative using Semantic Matching.
12
9 31
10 2
11 12
12 10
13 10
14 12
15 1
16 53
17 36
18 322

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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