Niranjana Sampathila
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Computer Vision and Pattern Recognition top 5%
- Health Information Management top 2%
- Virology top 5%
- Co-authors
- Krishnaraj ChadagaSrikanth PrabhuK. S. SwathiShashikiran UmakanthRajagopala ChadagaVivekananda Bhat KOliver FaustG. Muralidhar Bairy
- Topics
- Digital Imaging for Blood Diseases (21 papers)COVID-19 diagnosis using AI (19 papers)Artificial Intelligence in Healthcare (14 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsIEEE Access
- Partner nations
- IndiaAustraliaUnited States
In The Last Decade
Niranjana Sampathila
77 papers receiving 944 citations
Peers
Comparison fields: 5 of 122
- Artificial Intelligence 356
- Radiology, Nuclear Medicine and Imaging 311
- Computer Vision and Pattern Recognition 291
- Health Information Management 102
- Virology 94
Countries citing papers authored by Niranjana Sampathila
This map shows the geographic impact of Niranjana Sampathila'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 Niranjana Sampathila with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Niranjana Sampathila more than expected).
Fields of papers citing papers by Niranjana Sampathila
This network shows the impact of papers produced by Niranjana Sampathila. 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 Niranjana Sampathila. The network helps show where Niranjana Sampathila may publish in the future.
Co-authorship network of co-authors of Niranjana Sampathila
This figure shows the co-authorship network connecting the top 25 collaborators of Niranjana Sampathila. A scholar is included among the top collaborators of Niranjana Sampathila 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 Niranjana Sampathila. Niranjana Sampathila is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 5 | |
| 7 | 5 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 26 | |
| 11 | 17 | |
| 12 | 55 | |
| 13 | 19 | |
| 14 | 52 | |
| 15 | 1 | |
| 16 | 4 | |
| 17 | 24 | |
| 18 | 13 | |
| 19 | 10 | |
| 20 | 3 |
About Niranjana Sampathila
Niranjana Sampathila is a scholar working on Health Informatics, Health Information Management and Radiology, Nuclear Medicine and Imaging, having authored 85 papers that have together received 977 indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (21 papers), COVID-19 diagnosis using AI (19 papers) and Artificial Intelligence in Healthcare (14 papers). The work is most often cited by research in Health Informatics (75 citations), Health Information Management (102 citations) and Virology (94 citations). Niranjana Sampathila has collaborated with scholars based in India, Australia and United States. Frequent co-authors include Krishnaraj Chadaga, Srikanth Prabhu, K. S. Swathi, Shashikiran Umakanth, Rajagopala Chadaga, Vivekananda Bhat K, Oliver Faust, G. Muralidhar Bairy, U. Rajendra Acharya and Chinmay Chakraborty. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.
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.