G. Ramkumar
Impact in
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- Manufacturing Process and Optimization
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- Brain Tumor Detection and Classification
Papers in
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- AI in cancer detection 15
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- Infrared Thermography in Medicine 4
- Radiomics and Machine Learning in Medical Imaging 4
- COVID-19 diagnosis using AI 3
- Co-authors
- Biju Pottakkat (6 shared papers)Michael H. Goldwasser (1 shared paper)G. Sajiv (7 shared papers)Biswajit Dubashi (2 shared papers)Smita Kayal (1 shared paper)K. Selvi (1 shared paper)K. Kalaiselvi (1 shared paper)S. Rathika (1 shared paper)
- Journals
- Diagnostic Cytopathology (2 papers)Journal of Ultrasound in Medicine (1 paper)Artificial Intelligence in Medicine (1 paper)Multimedia Tools and Applications (1 paper)Journal of Clinical Oncology (1 paper)
- Partner nations
- IndiaJordanSaudi Arabia
In The Last Decade
G. Ramkumar
49 papers receiving 434 citations
Peers
Comparison fields: 5 of 102
- Industrial and Manufacturing Engineering 84
- Neurology 38
- Health Informatics 6
- Health Information Management 19
- Radiology, Nuclear Medicine and Imaging 69
Countries citing papers authored by G. Ramkumar
This map shows the geographic impact of G. Ramkumar'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 G. Ramkumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. Ramkumar more than expected).
Fields of papers citing papers by G. Ramkumar
This network shows the impact of papers produced by G. Ramkumar. 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 G. Ramkumar. The network helps show where G. Ramkumar may publish in the future.
Co-authors
The 25 scholars most cited alongside G. Ramkumar, 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 64 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 84 | |
| 2 | 1995 | 83 | |
| 3 | 2023 | 55 | |
| 4 | 2024 | 34 | |
| 5 | 2023 | 33 | |
| 6 | 2024 | 14 | |
| 7 | 2018 | 12 | |
| 8 | 2023 | 12 | |
| 9 | 2022 | 11 | |
| 10 | 2023 | 8 | |
| 11 | 2018 | 6 | |
| 12 | 2023 | 6 | |
| 13 | 2022 | 6 | |
| 14 | 2021 | 6 | |
| 15 | 2020 | 6 | |
| 16 | 2018 | 6 | |
| 17 | 2018 | 6 | |
| 18 | 2024 | 5 | |
| 19 | 2018 | 5 | |
| 20 | 2023 | 5 |
About G. Ramkumar
G. Ramkumar is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Surgery and Computer Networks and Communications, having authored 64 papers that have together received 458 indexed citations. Recurring topics across this work include AI in cancer detection (15 papers), Smart Systems and Machine Learning (8 papers), Brain Tumor Detection and Classification (7 papers), Infrastructure Maintenance and Monitoring (6 papers), Infrared Thermography in Medicine (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Digital Imaging for Blood Diseases (3 papers) and COVID-19 diagnosis using AI (3 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (84 citations), Neurology (38 citations), Health Informatics (6 citations), Health Information Management (19 citations) and Radiology, Nuclear Medicine and Imaging (69 citations). G. Ramkumar has collaborated with scholars based in India, Jordan and Saudi Arabia. Frequent co-authors include Biju Pottakkat, Michael H. Goldwasser, G. Sajiv, Biswajit Dubashi, Smita Kayal, K. Selvi, K. Kalaiselvi, S. Rathika, Prasanth Ganesan and T. J. Nagalakshmi. Their work appears in journals such as Diagnostic Cytopathology, Journal of Ultrasound in Medicine, Artificial Intelligence in Medicine, Multimedia Tools and Applications and Journal of Clinical Oncology.
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.