Pranab Sahoo
Impact in
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- Artificial Intelligence in Healthcare and Education
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- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
Papers in
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- AI in cancer detection 5
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- COVID-19 diagnosis using AI 5
- Radiomics and Machine Learning in Medical Imaging 1
- Co-authors
- Samrat Mondal (10 shared papers)Sriparna Saha (4 shared papers)Prolay Das (1 shared paper)Sriparna Saha (6 shared papers)Aman Chadha (3 shared papers)Manish Kumar (1 shared paper)Vinija Jain (2 shared papers)Manjeevan Seera (1 shared paper)
- Journals
- Journal of Agricultural and Food Chemistry (1 paper)Soft Computing (1 paper)IEEE Transactions on Consumer Electronics (1 paper)IEEE Access (1 paper)Biomedical Signal Processing and Control (1 paper)
- Partner nations
- IndiaUnited StatesMalaysia
In The Last Decade
Pranab Sahoo
14 papers receiving 106 citations
Peers
Comparison fields: 5 of 50
- Health Informatics 9
- Radiology, Nuclear Medicine and Imaging 36
- Artificial Intelligence 52
- General Dentistry 2
- Neurology 10
Countries citing papers authored by Pranab Sahoo
This map shows the geographic impact of Pranab Sahoo'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 Pranab Sahoo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pranab Sahoo more than expected).
Fields of papers citing papers by Pranab Sahoo
This network shows the impact of papers produced by Pranab Sahoo. 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 Pranab Sahoo. The network helps show where Pranab Sahoo may publish in the future.
Co-authors
The 16 scholars most cited alongside Pranab Sahoo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 23 | |
| 2 | 2023 | 19 | |
| 3 | 2024 | 13 | |
| 4 | 2023 | 12 | |
| 5 | 2022 | 9 | |
| 6 | 2022 | 8 | |
| 7 | 2022 | 6 | |
| 8 | 2024 | 4 | |
| 9 | 2024 | 3 | |
| 10 | Recent Local Sea Level Changes and its Impact on Geo- Environment of Purba Medinipur Coast, WB-A Geographical Analysis | 2014 | 3 |
| 11 | 2025 | 2 | |
| 12 | 2024 | 2 | |
| 13 | 2022 | 1 | |
| 14 | 2023 | 1 | |
| 15 | 2024 | 1 | |
| 16 | 2025 | 0 |
About Pranab Sahoo
Pranab Sahoo is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Molecular Biology, Computer Vision and Pattern Recognition and General Dentistry, having authored 16 papers that have together received 107 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (5 papers), AI in cancer detection (5 papers), Dental Research and COVID-19 (2 papers), Intraperitoneal and Appendiceal Malignancies (1 paper), Radiomics and Machine Learning in Medical Imaging (1 paper), Fisheries and Aquaculture Studies (1 paper), Gene expression and cancer classification (1 paper) and Brain Tumor Detection and Classification (1 paper). The work is most often cited by research in Health Informatics (9 citations), Radiology, Nuclear Medicine and Imaging (36 citations), Artificial Intelligence (52 citations), General Dentistry (2 citations) and Neurology (10 citations). Pranab Sahoo has collaborated with scholars based in India, United States and Malaysia. Frequent co-authors include Samrat Mondal, Sriparna Saha, Prolay Das, Sriparna Saha, Aman Chadha, Manish Kumar, Vinija Jain, Manjeevan Seera, Deepak Jain and Jyoti Prakash Singh. Their work appears in journals such as Journal of Agricultural and Food Chemistry, Soft Computing, IEEE Transactions on Consumer Electronics, IEEE Access and Biomedical Signal Processing and Control.
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.