Yan D. Zhao
- Molecular Biology top 5%
- Cancer Research top 2%
- Oncology top 10%
- Pulmonary and Respiratory Medicine top 5%
- Rheumatology top 2%
- Co-authors
- Rajagopal RameshBethany N. HannafonAnupama MunshiAllshine ChenRanganayaki MuralidharanNarsireddy AmreddyAkhil SrivastavaWilliam C. Dooley
- Topics
- Statistical Methods and Bayesian Inference (14 papers)Statistical Methods in Clinical Trials (11 papers)Statistical Methods and Inference (10 papers)
- Journals
- Proceedings of the National Academy of SciencesThe Journal of Experimental MedicineJournal of Clinical Oncology
- Partner nations
- United StatesChinaCanada
In The Last Decade
Yan D. Zhao
124 papers receiving 3.6k citations
Hit Papers
Peers
Comparison fields: 5 of 166
- Molecular Biology 1.6k
- Cancer Research 932
- Oncology 440
- Pulmonary and Respiratory Medicine 437
- Rheumatology 428
Countries citing papers authored by Yan D. Zhao
This map shows the geographic impact of Yan D. 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 Yan D. Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yan D. Zhao more than expected).
Fields of papers citing papers by Yan D. Zhao
This network shows the impact of papers produced by Yan D. 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 Yan D. Zhao. The network helps show where Yan D. Zhao may publish in the future.
Co-authorship network of co-authors of Yan D. Zhao
This figure shows the co-authorship network connecting the top 25 collaborators of Yan D. Zhao. A scholar is included among the top collaborators of Yan D. 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 Yan D. Zhao. Yan D. 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 | 1 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 4 | |
| 5 | 6 | |
| 6 | 5 | |
| 7 | 21 | |
| 8 | 43 | |
| 9 | 12 | |
| 10 | Epidemiological and clinical findings of discharge patients infected with the 2019 novel coronavirus (SARS-COV-2) in Changchun, Northeast China: A retrospective cohort study | 2 |
| 11 | 25 | |
| 12 | 69 | |
| 13 | 13 | |
| 14 | 14 | |
| 15 | 55 | |
| 16 | 41 | |
| 17 | 270 | |
| 18 | 1 | |
| 19 | 1 | |
| 20 | 19 |
About Yan D. Zhao
Yan D. Zhao is a scholar working on Statistics and Probability, Cancer Research and Oncology, having authored 139 papers that have together received 3.7k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (14 papers), Statistical Methods in Clinical Trials (11 papers) and Statistical Methods and Inference (10 papers). The work is most often cited by research in Cancer Research (932 citations), Rheumatology (428 citations) and Molecular Biology (1.6k citations). Yan D. Zhao has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Rajagopal Ramesh, Bethany N. Hannafon, Anupama Munshi, Allshine Chen, Ranganayaki Muralidharan, Narsireddy Amreddy, Akhil Srivastava, William C. Dooley, Anish Babu and Wei‐Qun Ding. Their work appears in journals such as Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine and Journal of Clinical Oncology.
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.