Stephen Skentzos
Impact in
- Family Practice top 10%
- Surgery top 10%
- Lipoproteins and Cardiovascular Health
Papers in
-
- Biomedical Text Mining and Ontologies 3
- Surgery 2
- Lipoproteins and Cardiovascular Health 2
- Co-authors
- Alexander Turchin (5 shared papers)Maria Shubina (3 shared papers)Jorge Plutzky (3 shared papers)Fritha Morrison (2 shared papers)Huabing Zhang (2 shared papers)Perry Mar (1 shared paper)Shervin Malmasi (2 shared papers)Rosalynn M. Nazarian (1 shared paper)
- Journals
- Journal of Vascular Surgery (1 paper)Applied Clinical Informatics (1 paper)American Journal of Nephrology (1 paper)Cardiorenal Medicine (1 paper)Annals of Internal Medicine (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Stephen Skentzos
7 papers receiving 543 citations
Stephen Skentzos's Hit Papers
Peers
Comparison fields: 5 of 60
- Family Practice 17
- Surgery 328
- Nephrology 39
- Geriatrics and Gerontology 18
- Health Informatics 6
Countries citing papers authored by Stephen Skentzos
This map shows the geographic impact of Stephen Skentzos'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 Stephen Skentzos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen Skentzos more than expected).
Fields of papers citing papers by Stephen Skentzos
This network shows the impact of papers produced by Stephen Skentzos. 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 Stephen Skentzos. The network helps show where Stephen Skentzos may publish in the future.
Co-authors
The 17 scholars most cited alongside Stephen Skentzos, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Discontinuation of Statins in Routine Care Settings Hit paper breakdown → | 2013 | 426 |
| 2 | 2013 | 54 | |
| 3 | 2017 | 26 | |
| 4 | Structured vs. unstructured: factors affecting adverse drug reaction documentation in an EMR repository. | 2011 | 23 |
| 5 | Extracting Healthcare Quality Information from Unstructured Data. | 2017 | 17 |
| 6 | 2014 | 9 | |
| 7 | 2013 | 1 |
About Stephen Skentzos
Stephen Skentzos is a scholar working on Molecular Biology, Surgery, Nephrology, Health Information Management and Toxicology, having authored 7 papers that have together received 556 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (3 papers), Lipoproteins and Cardiovascular Health (2 papers), Electronic Health Records Systems (1 paper), Pharmaceutical Economics and Policy (1 paper), Clinical practice guidelines implementation (1 paper), Pharmacovigilance and Adverse Drug Reactions (1 paper), Parathyroid Disorders and Treatments (1 paper) and Chronic Disease Management Strategies (1 paper). The work is most often cited by research in Family Practice (17 citations), Surgery (328 citations), Nephrology (39 citations), Geriatrics and Gerontology (18 citations) and Health Informatics (6 citations). Stephen Skentzos has collaborated with scholars based in United States and China. Frequent co-authors include Alexander Turchin, Maria Shubina, Jorge Plutzky, Fritha Morrison, Huabing Zhang, Perry Mar, Shervin Malmasi, Rosalynn M. Nazarian, Samir M. Parikh and Sagar U. Nigwekar. Their work appears in journals such as Journal of Vascular Surgery, Applied Clinical Informatics, American Journal of Nephrology, Cardiorenal Medicine and Annals of Internal Medicine.
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.