Kruthi Suvarna
About
In The Last Decade
Kruthi Suvarna
10 papers receiving 230 citations
Peers
Comparison fields: 5 of 77
- Molecular Biology 88
- Radiology, Nuclear Medicine and Imaging 69
- Artificial Intelligence 54
- Health Informatics 40
- Infectious Diseases 38
Countries citing papers authored by Kruthi Suvarna
This map shows the geographic impact of Kruthi Suvarna'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 Kruthi Suvarna with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kruthi Suvarna more than expected).
Fields of papers citing papers by Kruthi Suvarna
This network shows the impact of papers produced by Kruthi Suvarna. 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 Kruthi Suvarna. The network helps show where Kruthi Suvarna may publish in the future.
Co-authorship network of co-authors of Kruthi Suvarna
This figure shows the co-authorship network connecting the top 25 collaborators of Kruthi Suvarna. A scholar is included among the top collaborators of Kruthi Suvarna 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 Kruthi Suvarna. Kruthi Suvarna is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 26 | |
| 6 | 25 | |
| 7 | 25 | |
| 8 | 5 | |
| 9 | 126 | |
| 10 | 13 | |
| 11 | 9 |
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.