Kevin Krudys
- Molecular Biology
- Pediatrics, Perinatology and Child Health top 5%
- Cardiology and Cardiovascular Medicine top 10%
- Statistics and Probability top 5%
- Pharmacology top 10%
- Co-authors
- Yeruk MulugetaChristine GarnettGilbert J. BurckartGeorg FerberNenad SarapaCorina DotaJames J. KeirnsSteve Riley
- Topics
- Pharmaceutical studies and practices (7 papers)Statistical Methods in Clinical Trials (6 papers)Pharmacogenetics and Drug Metabolism (4 papers)
- Journals
- Journal of Controlled ReleaseAmerican Journal of Obstetrics and GynecologyAmerican Journal of Physiology-Endocrinology and Metabolism
- Partner nations
- United StatesUnited KingdomNetherlands
In The Last Decade
Kevin Krudys
20 papers receiving 762 citations
Peers
Comparison fields: 5 of 107
- Molecular Biology 202
- Pediatrics, Perinatology and Child Health 192
- Cardiology and Cardiovascular Medicine 175
- Statistics and Probability 116
- Pharmacology 100
Countries citing papers authored by Kevin Krudys
This map shows the geographic impact of Kevin Krudys'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 Kevin Krudys with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Krudys more than expected).
Fields of papers citing papers by Kevin Krudys
This network shows the impact of papers produced by Kevin Krudys. 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 Kevin Krudys. The network helps show where Kevin Krudys may publish in the future.
Co-authorship network of co-authors of Kevin Krudys
This figure shows the co-authorship network connecting the top 25 collaborators of Kevin Krudys. A scholar is included among the top collaborators of Kevin Krudys 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 Kevin Krudys. Kevin Krudys is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 5 | |
| 4 | 4 | |
| 5 | 79 | |
| 6 | 84 | |
| 7 | 5 | |
| 8 | 58 | |
| 9 | 62 | |
| 10 | 141 | |
| 11 | 68 | |
| 12 | 81 | |
| 13 | 6 | |
| 14 | 112 | |
| 15 | 32 | |
| 16 | 3 | |
| 17 | 2 | |
| 18 | 16 | |
| 19 | 22 | |
| 20 | 9 |
About Kevin Krudys
Kevin Krudys is a scholar working on Statistics and Probability, Pharmacology and Pediatrics, Perinatology and Child Health, having authored 20 papers that have together received 792 indexed citations. Recurring topics across this work include Pharmaceutical studies and practices (7 papers), Statistical Methods in Clinical Trials (6 papers) and Pharmacogenetics and Drug Metabolism (4 papers). The work is most often cited by research in Statistics and Probability (116 citations), Pharmacology (92 citations) and Pediatrics, Perinatology and Child Health (192 citations). Kevin Krudys has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Yeruk Mulugeta, Christine Garnett, Gilbert J. Burckart, Georg Ferber, Nenad Sarapa, Corina Dota, James J. Keirns, Steve Riley, Charles Benson and Catherine Ortemann‐Renon. Their work appears in journals such as Journal of Controlled Release, American Journal of Obstetrics and Gynecology and American Journal of Physiology-Endocrinology and Metabolism.
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.