Katya L Masconi
- Pulmonary and Respiratory Medicine
- Cardiology and Cardiovascular Medicine
- Surgery
- Endocrinology, Diabetes and Metabolism
- Obstetrics and Gynecology top 10%
- Co-authors
- André Pascal KengneTandi E. MatshaRajiv T. ErasmusAngela WoodMichael SweetingJanet T. PowellPinar UlugSimon G. Thompson
- Topics
- Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers)Genetic Associations and Epidemiology (4 papers)Liver Disease Diagnosis and Treatment (3 papers)
- Cited by
- Obstetrics and GynecologyCardiology and Cardiovascular MedicinePulmonary and Respiratory Medicine
- Partner nations
- South AfricaUnited KingdomUnited States
In The Last Decade
Katya L Masconi
17 papers receiving 496 citations
Peers
Comparison fields: 5 of 96
- Pulmonary and Respiratory Medicine 167
- Cardiology and Cardiovascular Medicine 123
- Surgery 108
- Endocrinology, Diabetes and Metabolism 76
- Obstetrics and Gynecology 69
Countries citing papers authored by Katya L Masconi
This map shows the geographic impact of Katya L Masconi'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 Katya L Masconi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Katya L Masconi more than expected).
Fields of papers citing papers by Katya L Masconi
This network shows the impact of papers produced by Katya L Masconi. 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 Katya L Masconi. The network helps show where Katya L Masconi may publish in the future.
Co-authorship network of co-authors of Katya L Masconi
This figure shows the co-authorship network connecting the top 25 collaborators of Katya L Masconi. A scholar is included among the top collaborators of Katya L Masconi 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 Katya L Masconi. Katya L Masconi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 51 | |
| 3 | 102 | |
| 4 | 18 | |
| 5 | 27 | |
| 6 | 60 | |
| 7 | 23 | |
| 8 | 22 | |
| 9 | 80 | |
| 10 | 6 | |
| 11 | 13 | |
| 12 | 18 | |
| 13 | 35 | |
| 14 | 2 | |
| 15 | 15 | |
| 16 | 20 | |
| 17 | 8 |
About Katya L Masconi
Katya L Masconi is a scholar working on Endocrinology, Diabetes and Metabolism, Nephrology and Obstetrics and Gynecology, having authored 17 papers that have together received 503 indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers), Genetic Associations and Epidemiology (4 papers) and Liver Disease Diagnosis and Treatment (3 papers). The work is most often cited by research in Obstetrics and Gynecology (69 citations), Cardiology and Cardiovascular Medicine (123 citations) and Pulmonary and Respiratory Medicine (167 citations). Katya L Masconi has collaborated with scholars based in South Africa, United Kingdom and United States. Frequent co-authors include André Pascal Kengne, Tandi E. Matsha, Rajiv T. Erasmus, Angela Wood, Michael Sweeting, Janet T. Powell, Pinar Ulug, Simon G. Thompson, Edmund Jones and Matthew Glover. Their work appears in journals such as The Lancet, PLoS ONE and International 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.