Donna K. Pauler
- Pulmonary and Respiratory Medicine top 2%
- Molecular Biology
- Surgery top 10%
- Oncology top 10%
- Statistics and Probability top 1%
- Co-authors
- Phyllis J. GoodmanJohn J. CrowleyIan M. ThompsonCatherine M. TangenM. Scott LuciaScott M. LippmanLori M. MinasianHoward L. Parnes
- Topics
- Bayesian Methods and Mixture Models (7 papers)Statistical Methods and Inference (6 papers)Statistical Methods and Bayesian Inference (5 papers)
- Journals
- New England Journal of MedicineJournal of Clinical OncologyJournal of the American Statistical Association
- Partner nations
- United StatesTürkiyeDenmark
In The Last Decade
Donna K. Pauler
27 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 160
- Pulmonary and Respiratory Medicine 1.4k
- Molecular Biology 517
- Surgery 422
- Oncology 418
- Statistics and Probability 409
Countries citing papers authored by Donna K. Pauler
This map shows the geographic impact of Donna K. Pauler'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 Donna K. Pauler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Donna K. Pauler more than expected).
Fields of papers citing papers by Donna K. Pauler
This network shows the impact of papers produced by Donna K. Pauler. 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 Donna K. Pauler. The network helps show where Donna K. Pauler may publish in the future.
Co-authorship network of co-authors of Donna K. Pauler
This figure shows the co-authorship network connecting the top 25 collaborators of Donna K. Pauler. A scholar is included among the top collaborators of Donna K. Pauler 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 Donna K. Pauler. Donna K. Pauler is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 81 | |
| 2 | 85 | |
| 3 | 3 | |
| 4 | Prevalence of Prostate Cancer among Men with a Prostate-Specific Antigen Level ≤4.0 ng per Milliliterbreakdown → | 1738 |
| 5 | 15 | |
| 6 | 68 | |
| 7 | 46 | |
| 8 | 12 | |
| 9 | 11 | |
| 10 | Factors influencing serum CA125II levels in healthy postmenopausal women. | 97 |
| 11 | 11 | |
| 12 | 53 | |
| 13 | 44 | |
| 14 | 107 | |
| 15 | 7 | |
| 16 | 12 | |
| 17 | 12 | |
| 18 | 13 | |
| 19 | 31 | |
| 20 | 4 |
About Donna K. Pauler
Donna K. Pauler is a scholar working on Statistics and Probability, Artificial Intelligence and Pathology and Forensic Medicine, having authored 27 papers that have together received 2.8k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (7 papers), Statistical Methods and Inference (6 papers) and Statistical Methods and Bayesian Inference (5 papers). The work is most often cited by research in Statistics and Probability (409 citations), Pulmonary and Respiratory Medicine (1.4k citations) and Reproductive Medicine (178 citations). Donna K. Pauler has collaborated with scholars based in United States, Türkiye and Denmark. Frequent co-authors include Phyllis J. Goodman, John J. Crowley, Ian M. Thompson, Catherine M. Tangen, M. Scott Lucia, Scott M. Lippman, Lori M. Minasian, Howard L. Parnes, E. David Crawford and Charles A. Coltman. Their work appears in journals such as New England Journal of Medicine, Journal of Clinical Oncology 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.