Ann Marie Návar
- Surgery top 1%
- Cardiology and Cardiovascular Medicine top 1%
- Economics and Econometrics top 1%
- Epidemiology top 5%
- Endocrinology, Diabetes and Metabolism top 1%
- Co-authors
- Michael PencinaBenjamin A. GoldsteinEric D. PetersonJohn P. A. IoannidisRickey E. CarterSalim S. ViraniAllan D. SnidermanTracy Y. Wang
- Topics
- Lipoproteins and Cardiovascular Health (74 papers)Health Systems, Economic Evaluations, Quality of Life (48 papers)Pharmaceutical Economics and Policy (27 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Ann Marie Návar
150 papers receiving 5.3k citations
Hit Papers
Peers
Comparison fields: 5 of 171
- Surgery 1.8k
- Cardiology and Cardiovascular Medicine 1.4k
- Economics and Econometrics 977
- Epidemiology 920
- Endocrinology, Diabetes and Metabolism 857
Countries citing papers authored by Ann Marie Návar
This map shows the geographic impact of Ann Marie Návar'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 Ann Marie Návar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ann Marie Návar more than expected).
Fields of papers citing papers by Ann Marie Návar
This network shows the impact of papers produced by Ann Marie Návar. 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 Ann Marie Návar. The network helps show where Ann Marie Návar may publish in the future.
Co-authorship network of co-authors of Ann Marie Návar
This figure shows the co-authorship network connecting the top 25 collaborators of Ann Marie Návar. A scholar is included among the top collaborators of Ann Marie Návar 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 Ann Marie Návar. Ann Marie Návar 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 | 1 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 12 | |
| 11 | 5 | |
| 12 | 36 | |
| 13 | 3 | |
| 14 | 9 | |
| 15 | 9 | |
| 16 | 1 | |
| 17 | 21 | |
| 18 | 0 | |
| 19 | 16 | |
| 20 | Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic reviewbreakdown → | 548 |
About Ann Marie Návar
Ann Marie Návar is a scholar working on Cardiology and Cardiovascular Medicine, Economics and Econometrics and Endocrinology, Diabetes and Metabolism, having authored 167 papers that have together received 5.4k indexed citations. Recurring topics across this work include Lipoproteins and Cardiovascular Health (74 papers), Health Systems, Economic Evaluations, Quality of Life (48 papers) and Pharmaceutical Economics and Policy (27 papers). The work is most often cited by research in Health Informatics (116 citations), Health (570 citations) and Cardiology and Cardiovascular Medicine (1.4k citations). Ann Marie Návar has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Michael Pencina, Benjamin A. Goldstein, Eric D. Peterson, John P. A. Ioannidis, Rickey E. Carter, Salim S. Virani, Allan D. Sniderman, Tracy Y. Wang, Jennifer G. Robinson and Michael G. Nanna. Their work appears in journals such as New England Journal of Medicine, JAMA and Circulation.
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.