S. Prabha
Impact in
- Neurology top 10%
- Brain Tumor Detection and Classification
-
- Artificial Intelligence in Healthcare
Papers in
-
- Retinal Imaging and Analysis 8
- Infrared Thermography in Medicine 6
- COVID-19 diagnosis using AI 5
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- Digital Imaging for Blood Diseases 5
- Medical Image Segmentation Techniques 5
- Co-authors
- C. M. Sujatha (5 shared papers)K. Sakthidasan Sankaran (7 shared papers)K. Vijayakumar (7 shared papers)K. Vijayakumar (6 shared papers)R. Geetha (2 shared papers)Ramakrishnan Swaminathan (1 shared paper)M. Sasikala (1 shared paper)Peeta Basa Pati (1 shared paper)
- Journals
- Neural Computing and Applications (1 paper)Applied Soft Computing (1 paper)Technology and Health Care (1 paper)International Journal of Neuroscience (1 paper)Cluster Computing (1 paper)
- Partner nations
- IndiaUnited StatesMalaysia
In The Last Decade
S. Prabha
43 papers receiving 311 citations
Peers
Comparison fields: 5 of 68
- Neurology 105
- Health Information Management 52
- Radiology, Nuclear Medicine and Imaging 98
- Computer Vision and Pattern Recognition 66
- Artificial Intelligence 84
Countries citing papers authored by S. Prabha
This map shows the geographic impact of S. Prabha'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 S. Prabha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Prabha more than expected).
Fields of papers citing papers by S. Prabha
This network shows the impact of papers produced by S. Prabha. 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 S. Prabha. The network helps show where S. Prabha may publish in the future.
Co-authors
The 25 scholars most cited alongside S. Prabha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 88 | |
| 2 | 2020 | 26 | |
| 3 | 2024 | 18 | |
| 4 | 2021 | 15 | |
| 5 | 2014 | 15 | |
| 6 | 2014 | 13 | |
| 7 | 2023 | 13 | |
| 8 | 2024 | 12 | |
| 9 | 2018 | 12 | |
| 10 | 2024 | 10 | |
| 11 | Texture Classification Using Curvelet Transform | 2013 | 10 |
| 12 | 2024 | 9 | |
| 13 | 2019 | 7 | |
| 14 | 2024 | 6 | |
| 15 | 2024 | 6 | |
| 16 | 2024 | 4 | |
| 17 | 2018 | 4 | |
| 18 | 2020 | 4 | |
| 19 | 2024 | 4 | |
| 20 | 2024 | 4 |
About S. Prabha
S. Prabha is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Artificial Intelligence, Neurology and Mechanics of Materials, having authored 58 papers that have together received 326 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (8 papers), Brain Tumor Detection and Classification (8 papers), AI in cancer detection (7 papers), Infrared Thermography in Medicine (6 papers), Digital Imaging for Blood Diseases (5 papers), Medical Image Segmentation Techniques (5 papers), Thermography and Photoacoustic Techniques (5 papers) and COVID-19 diagnosis using AI (5 papers). The work is most often cited by research in Neurology (105 citations), Health Information Management (52 citations), Radiology, Nuclear Medicine and Imaging (98 citations), Computer Vision and Pattern Recognition (66 citations) and Artificial Intelligence (84 citations). S. Prabha has collaborated with scholars based in India, United States and Malaysia. Frequent co-authors include C. M. Sujatha, K. Sakthidasan Sankaran, K. Vijayakumar, K. Vijayakumar, R. Geetha, Ramakrishnan Swaminathan, M. Sasikala, Peeta Basa Pati, Ramya Mohan and V. Rajinikanth. Their work appears in journals such as Neural Computing and Applications, Applied Soft Computing, Technology and Health Care, International Journal of Neuroscience and Cluster Computing.
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.