J. Dheeba
Impact in
- Health Informatics top 10%
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- Artificial Intelligence in Healthcare
Papers in
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- AI in cancer detection 8
- Neural Networks and Applications 3
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- Image Retrieval and Classification Techniques 3
- Co-authors
- S. Tamil Selvi (5 shared papers)Nikita Singh (3 shared papers)T. Jaya (2 shared papers)C. Sathiya Kumar (1 shared paper)Bharath Ramesh (1 shared paper)R. Raja Singh (1 shared paper)
In The Last Decade
J. Dheeba
22 papers receiving 451 citations
Peers
Comparison fields: 5 of 76
- Health Informatics 17
- Health Information Management 57
- Radiology, Nuclear Medicine and Imaging 230
- Artificial Intelligence 315
- Computer Vision and Pattern Recognition 185
Countries citing papers authored by J. Dheeba
This map shows the geographic impact of J. Dheeba'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 J. Dheeba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Dheeba more than expected).
Fields of papers citing papers by J. Dheeba
This network shows the impact of papers produced by J. Dheeba. 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 J. Dheeba. The network helps show where J. Dheeba may publish in the future.
Co-authors
The 6 scholars most cited alongside J. Dheeba, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 267 | |
| 2 | 2015 | 56 | |
| 3 | 2011 | 37 | |
| 4 | 2011 | 32 | |
| 5 | 2011 | 21 | |
| 6 | 2022 | 13 | |
| 7 | 2015 | 11 | |
| 8 | 2010 | 11 | |
| 9 | 2024 | 9 | |
| 10 | 2017 | 6 | |
| 11 | 2013 | 5 | |
| 12 | 2007 | 5 | |
| 13 | 2022 | 4 | |
| 14 | 2020 | 4 | |
| 15 | 2022 | 4 | |
| 16 | 2019 | 3 | |
| 17 | 2023 | 2 | |
| 18 | 2023 | 2 | |
| 19 | 2023 | 1 | |
| 20 | 2015 | 1 |
About J. Dheeba
J. Dheeba is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Computer Networks and Communications and Molecular Biology, having authored 25 papers that have together received 496 indexed citations. Recurring topics across this work include AI in cancer detection (8 papers), Retinal Imaging and Analysis (4 papers), Neural Networks and Applications (3 papers), Image Retrieval and Classification Techniques (3 papers), Gene expression and cancer classification (3 papers), Glaucoma and retinal disorders (2 papers), Energy Efficient Wireless Sensor Networks (2 papers) and Brain Tumor Detection and Classification (2 papers). The work is most often cited by research in Health Informatics (17 citations), Health Information Management (57 citations), Radiology, Nuclear Medicine and Imaging (230 citations), Artificial Intelligence (315 citations) and Computer Vision and Pattern Recognition (185 citations). J. Dheeba has collaborated with scholars based in India, Mexico and Germany. Frequent co-authors include S. Tamil Selvi, Nikita Singh, T. Jaya, C. Sathiya Kumar, Bharath Ramesh and R. Raja Singh. Their work appears in journals such as Journal of Medical Systems, Journal of Digital Imaging, Journal of Biomedical Informatics, Indian Journal of Science and Technology and Wireless Personal Communications.
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.