Mei‐Cheng Wang
- Statistics and Probability top 0.1%
- Psychiatry and Mental health top 1%
- Public Health, Environmental and Occupational Health top 1%
- Physiology top 5%
- Pulmonary and Respiratory Medicine top 5%
- Co-authors
- Nicholas P. JewellMarilyn AlbertChiung‐Yu HuangAnja SoldanCorinne PettigrewAbhay MoghekarAbimereki D. MuzaaleDorry L. Segev
- Topics
- Statistical Methods and Inference (48 papers)Statistical Methods and Bayesian Inference (35 papers)Dementia and Cognitive Impairment Research (31 papers)
- Partner nations
- United StatesTaiwanChina
In The Last Decade
Mei‐Cheng Wang
125 papers receiving 5.9k citations
Hit Papers
Peers
Comparison fields: 5 of 177
- Statistics and Probability 1.6k
- Psychiatry and Mental health 1.1k
- Public Health, Environmental and Occupational Health 1.1k
- Physiology 746
- Pulmonary and Respiratory Medicine 567
Countries citing papers authored by Mei‐Cheng Wang
This map shows the geographic impact of Mei‐Cheng Wang'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 Mei‐Cheng Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mei‐Cheng Wang more than expected).
Fields of papers citing papers by Mei‐Cheng Wang
This network shows the impact of papers produced by Mei‐Cheng Wang. 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 Mei‐Cheng Wang. The network helps show where Mei‐Cheng Wang may publish in the future.
Co-authorship network of co-authors of Mei‐Cheng Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Mei‐Cheng Wang. A scholar is included among the top collaborators of Mei‐Cheng Wang 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 Mei‐Cheng Wang. Mei‐Cheng Wang 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 | 19 | |
| 3 | 6 | |
| 4 | 34 | |
| 5 | 3 | |
| 6 | 6 | |
| 7 | 60 | |
| 8 | 25 | |
| 9 | 6 | |
| 10 | 2 | |
| 11 | 7 | |
| 12 | 7 | |
| 13 | 59 | |
| 14 | 14 | |
| 15 | 6 | |
| 16 | 9 | |
| 17 | 17 | |
| 18 | 107 | |
| 19 | 63 | |
| 20 | 12 |
About Mei‐Cheng Wang
Mei‐Cheng Wang is a scholar working on Statistics and Probability, Psychiatry and Mental health and Physiology, having authored 134 papers that have together received 6.0k indexed citations. Recurring topics across this work include Statistical Methods and Inference (48 papers), Statistical Methods and Bayesian Inference (35 papers) and Dementia and Cognitive Impairment Research (31 papers). The work is most often cited by research in Statistics and Probability (1.6k citations), Psychiatry and Mental health (1.1k citations) and Transplantation (166 citations). Mei‐Cheng Wang has collaborated with scholars based in United States, Taiwan and China. Frequent co-authors include Nicholas P. Jewell, Marilyn Albert, Chiung‐Yu Huang, Anja Soldan, Corinne Pettigrew, Abhay Moghekar, Abimereki D. Muzaale, Dorry L. Segev, Wei‐Yann Tsai and J.L. Wainright. Their work appears in journals such as JAMA, Journal of the American Statistical Association and Annals of Internal Medicine.
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.