Shuying Shen
- Artificial Intelligence top 1%
- Molecular Biology top 10%
- Health Information Management top 0.5%
- Management Science and Operations Research top 5%
- Epidemiology
- Co-authors
- Brett R. SouthÖzlem UzunerScott L. DuVallMatthew H. SamoreStéphane M. MeystreLP SamaranayakeHK YipAdi V. Gundlapalli
- Topics
- Biomedical Text Mining and Ontologies (20 papers)Topic Modeling (16 papers)Electronic Health Records Systems (11 papers)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Shuying Shen
50 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 145
- Artificial Intelligence 1.3k
- Molecular Biology 1.0k
- Health Information Management 270
- Management Science and Operations Research 153
- Epidemiology 139
Countries citing papers authored by Shuying Shen
This map shows the geographic impact of Shuying 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 Shuying Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuying Shen more than expected).
Fields of papers citing papers by Shuying Shen
This network shows the impact of papers produced by Shuying 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 Shuying Shen. The network helps show where Shuying Shen may publish in the future.
Co-authorship network of co-authors of Shuying Shen
This figure shows the co-authorship network connecting the top 25 collaborators of Shuying Shen. A scholar is included among the top collaborators of Shuying 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 Shuying Shen. Shuying Shen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 17 | |
| 7 | 123 | |
| 8 | 22 | |
| 9 | 7 | |
| 10 | 116 | |
| 11 | A Hybrid Stepwise Approach for De-identifying Person Names in Clinical Documents | 7 |
| 12 | A Prototype Tool Set to Support Machine-Assisted Annotation | 29 |
| 13 | On the Road Towards Developing a Publicly Available Corpus of De-identified Clinical Texts. | 1 |
| 14 | 57 | |
| 15 | 4 | |
| 16 | 81 | |
| 17 | 9 | |
| 18 | 41 | |
| 19 | 5 | |
| 20 | 70 |
About Shuying Shen
Shuying Shen is a scholar working on Health Information Management, Microbiology and Issues, ethics and legal aspects, having authored 55 papers that have together received 2.1k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (20 papers), Topic Modeling (16 papers) and Electronic Health Records Systems (11 papers). The work is most often cited by research in Health Information Management (270 citations), Artificial Intelligence (1.3k citations) and Health Informatics (51 citations). Shuying Shen has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Brett R. South, Özlem Uzuner, Scott L. DuVall, Matthew H. Samore, Stéphane M. Meystre, LP Samaranayake, HK Yip, Adi V. Gundlapalli, Óscar Ferrández and Nannan Gao. Their work appears in journals such as ACS Nano, PLoS ONE and Advanced Functional Materials.
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.