William C. Louv
- Microbiology top 1%
- Epidemiology
- General Health Professions top 10%
- Public Health, Environmental and Occupational Health
- Infectious Diseases
- Co-authors
- W. James AlexanderHarland AustinFabio BarboneW. Dana FlandersSergio StagnoJeffrey A. PerlmanJeffrey M. RosemanRamon C. Littell
- Topics
- Reproductive tract infections research (4 papers)Statistical Methods and Bayesian Inference (3 papers)Reproductive Health and Contraception (3 papers)
- Journals
- Journal of the American Statistical AssociationTechnometricsAmerican Journal of Epidemiology
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
William C. Louv
21 papers receiving 533 citations
Peers
Comparison fields: 5 of 99
- Microbiology 298
- Epidemiology 172
- General Health Professions 166
- Public Health, Environmental and Occupational Health 133
- Infectious Diseases 82
Countries citing papers authored by William C. Louv
This map shows the geographic impact of William C. Louv'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 William C. Louv with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William C. Louv more than expected).
Fields of papers citing papers by William C. Louv
This network shows the impact of papers produced by William C. Louv. 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 William C. Louv. The network helps show where William C. Louv may publish in the future.
Co-authorship network of co-authors of William C. Louv
This figure shows the co-authorship network connecting the top 25 collaborators of William C. Louv. A scholar is included among the top collaborators of William C. Louv 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 William C. Louv. William C. Louv is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Association of HLA phenotypes with hypertension in African Americans and Caucasoid Americans with type II diabetes, a population at risk for renal disease. | 3 |
| 2 | 6 | |
| 3 | 6 | |
| 4 | 150 | |
| 5 | 96 | |
| 6 | 98 | |
| 7 | 2 | |
| 8 | Detection of diabetic retinopathy by optometrists. | 27 |
| 9 | 10 | |
| 10 | 38 | |
| 11 | 1 | |
| 12 | 54 | |
| 13 | 37 | |
| 14 | 4 | |
| 15 | 10 | |
| 16 | 3 | |
| 17 | 3 | |
| 18 | 8 | |
| 19 | 4 | |
| 20 | 1 |
About William C. Louv
William C. Louv is a scholar working on Statistics and Probability, Microbiology and Management Science and Operations Research, having authored 21 papers that have together received 564 indexed citations. Recurring topics across this work include Reproductive tract infections research (4 papers), Statistical Methods and Bayesian Inference (3 papers) and Reproductive Health and Contraception (3 papers). The work is most often cited by research in Microbiology (298 citations), Periodontics (33 citations) and General Health Professions (166 citations). William C. Louv has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include W. James Alexander, Harland Austin, Fabio Barbone, W. Dana Flanders, Sergio Stagno, Jeffrey A. Perlman, Jeffrey M. Roseman, Ramon C. Littell, Rodney C.P. Go and Ronald T. Acton. Their work appears in journals such as Journal of the American Statistical Association, Technometrics and American Journal of Epidemiology.
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.