Nina Vasavada
About
In The Last Decade
Nina Vasavada
9 papers receiving 543 citations
Peers
Comparison fields: 5 of 78
- Nephrology 211
- Hematology 145
- Cardiology and Cardiovascular Medicine 119
- Endocrinology, Diabetes and Metabolism 109
- Molecular Biology 93
Countries citing papers authored by Nina Vasavada
This map shows the geographic impact of Nina Vasavada'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 Nina Vasavada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nina Vasavada more than expected).
Fields of papers citing papers by Nina Vasavada
This network shows the impact of papers produced by Nina Vasavada. 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 Nina Vasavada. The network helps show where Nina Vasavada may publish in the future.
Co-authorship network of co-authors of Nina Vasavada
This figure shows the co-authorship network connecting the top 25 collaborators of Nina Vasavada. A scholar is included among the top collaborators of Nina Vasavada 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 Nina Vasavada. Nina Vasavada is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 8 | |
| 3 | 66 | |
| 4 | 100 | |
| 5 | 218 | |
| 6 | 12 | |
| 7 | 37 | |
| 8 | 90 | |
| 9 | 21 |
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.