Shan Zhao
- Infectious Diseases top 2%
- Molecular Biology
- Neurology top 5%
- Cardiology and Cardiovascular Medicine top 10%
- Oncology top 10%
- Co-authors
- Ravi IyengarBenjamin S. GlicksbergGirish N. NadkarniAdam RussakJagat NarulaMatthew A. LevinAlexander W. CharneyAnuradha Lala
- Topics
- Computational Drug Discovery Methods (4 papers)COVID-19 Clinical Research Studies (4 papers)Bioinformatics and Genomic Networks (3 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American College of CardiologyPLoS ONE
- Partner nations
- United StatesChinaGermany
In The Last Decade
Shan Zhao
24 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 128
- Infectious Diseases 610
- Molecular Biology 555
- Neurology 366
- Cardiology and Cardiovascular Medicine 290
- Oncology 273
Countries citing papers authored by Shan Zhao
This map shows the geographic impact of Shan Zhao'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 Shan Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shan Zhao more than expected).
Fields of papers citing papers by Shan Zhao
This network shows the impact of papers produced by Shan Zhao. 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 Shan Zhao. The network helps show where Shan Zhao may publish in the future.
Co-authorship network of co-authors of Shan Zhao
This figure shows the co-authorship network connecting the top 25 collaborators of Shan Zhao. A scholar is included among the top collaborators of Shan Zhao 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 Shan Zhao. Shan Zhao 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 | 2 | |
| 3 | 6 | |
| 4 | 6 | |
| 5 | 11 | |
| 6 | 60 | |
| 7 | 19 | |
| 8 | 12 | |
| 9 | Association of Treatment Dose Anticoagulation With In-Hospital Survival Among Hospitalized Patients With COVID-19breakdown → | 622 |
| 10 | 74 | |
| 11 | 22 | |
| 12 | 24 | |
| 13 | 57 | |
| 14 | 40 | |
| 15 | 2 | |
| 16 | 19 | |
| 17 | 120 | |
| 18 | 13 | |
| 19 | 164 | |
| 20 | 11 |
About Shan Zhao
Shan Zhao is a scholar working on Health Informatics, Health Information Management and Pharmacology, having authored 25 papers that have together received 1.8k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (4 papers), COVID-19 Clinical Research Studies (4 papers) and Bioinformatics and Genomic Networks (3 papers). The work is most often cited by research in Internal Medicine (213 citations), Infectious Diseases (610 citations) and Neurology (366 citations). Shan Zhao has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Ravi Iyengar, Benjamin S. Glicksberg, Girish N. Nadkarni, Adam Russak, Jagat Narula, Matthew A. Levin, Alexander W. Charney, Anuradha Lala, Valentı́n Fuster and Zahi A. Fayad. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American College of Cardiology and PLoS ONE.
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.