Michael R. Chernick
- Cardiology and Cardiovascular Medicine top 5%
- Statistics and Probability top 1%
- Internal Medicine top 2%
- Molecular Biology
- Economics and Econometrics top 5%
- Co-authors
- Robert A LaBuddeStuart J. ConnollyMichael D. EzekowitzAmit ParekhSalim YusufSean YangPaul ReillyDuke Bahn
- Topics
- Advanced Statistical Methods and Models (16 papers)Statistical Methods and Inference (15 papers)Bayesian Methods and Mixture Models (8 papers)
- Journals
- CirculationSHILAP Revista de lepidopterologíaJournal of the American Statistical Association
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
Michael R. Chernick
64 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 217
- Cardiology and Cardiovascular Medicine 535
- Statistics and Probability 458
- Internal Medicine 253
- Molecular Biology 248
- Economics and Econometrics 238
Countries citing papers authored by Michael R. Chernick
This map shows the geographic impact of Michael R. Chernick'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 Michael R. Chernick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael R. Chernick more than expected).
Fields of papers citing papers by Michael R. Chernick
This network shows the impact of papers produced by Michael R. Chernick. 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 Michael R. Chernick. The network helps show where Michael R. Chernick may publish in the future.
Co-authorship network of co-authors of Michael R. Chernick
This figure shows the co-authorship network connecting the top 25 collaborators of Michael R. Chernick. A scholar is included among the top collaborators of Michael R. Chernick 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 Michael R. Chernick. Michael R. Chernick is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 51 | |
| 2 | 10 | |
| 3 | 14 | |
| 4 | 28 | |
| 5 | 54 | |
| 6 | 45 | |
| 7 | 73 | |
| 8 | 14 | |
| 9 | 73 | |
| 10 | 183 | |
| 11 | 215 | |
| 12 | 15 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 11 | |
| 16 | 1 | |
| 17 | 1 | |
| 18 | 2 | |
| 19 | 3 | |
| 20 | 57 |
About Michael R. Chernick
Michael R. Chernick is a scholar working on Statistics and Probability, Mathematical Physics and Statistics, Probability and Uncertainty, having authored 67 papers that have together received 3.4k indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (16 papers), Statistical Methods and Inference (15 papers) and Bayesian Methods and Mixture Models (8 papers). The work is most often cited by research in Internal Medicine (253 citations), Statistics and Probability (458 citations) and Cardiology and Cardiovascular Medicine (535 citations). Michael R. Chernick has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Robert A LaBudde, Stuart J. Connolly, Michael D. Ezekowitz, Amit Parekh, Salim Yusuf, Sean Yang, Paul Reilly, Duke Bahn, Fred Lee and Anil Kumar. Their work appears in journals such as Circulation, SHILAP Revista de lepidopterología and Journal of the American Statistical Association.
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.