Debendra Muduli
Impact in
- Neurology top 10%
- Brain Tumor Detection and Classification
- Artificial Intelligence top 5%
- AI in cancer detection
- Machine Learning and ELM
Papers in
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- Digital Imaging for Blood Diseases 6
- Face and Expression Recognition 3
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- AI in cancer detection 6
- Machine Learning and ELM 5
- Co-authors
- Banshidhar Majhi (4 shared papers)Ratnakar Dash (4 shared papers)Rakesh Ranjan Kumar (5 shared papers)Jitesh Pradhan (2 shared papers)Abhinav Kumar (2 shared papers)Nikhat Parveen (6 shared papers)Santosh Kumar Sharma (9 shared papers)Sultan M. Alanazi (2 shared papers)
- Journals
- IEEE Access (4 papers)Results in Engineering (3 papers)Biomedical Signal Processing and Control (3 papers)Scientific Reports (1 paper)Array (1 paper)
- Partner nations
- IndiaLebanonSaudi Arabia
In The Last Decade
Debendra Muduli
30 papers receiving 377 citations
Peers
Comparison fields: 5 of 62
- Neurology 109
- Artificial Intelligence 250
- Radiology, Nuclear Medicine and Imaging 171
- Health Information Management 34
- Computer Vision and Pattern Recognition 106
Countries citing papers authored by Debendra Muduli
This map shows the geographic impact of Debendra Muduli'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 Debendra Muduli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Debendra Muduli more than expected).
Fields of papers citing papers by Debendra Muduli
This network shows the impact of papers produced by Debendra Muduli. 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 Debendra Muduli. The network helps show where Debendra Muduli may publish in the future.
Co-authors
The 25 scholars most cited alongside Debendra Muduli, 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 44 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 110 | |
| 2 | 2020 | 106 | |
| 3 | 2021 | 49 | |
| 4 | 2023 | 32 | |
| 5 | 2023 | 20 | |
| 6 | 2023 | 15 | |
| 7 | 2024 | 7 | |
| 8 | 2023 | 6 | |
| 9 | 2023 | 6 | |
| 10 | 2024 | 4 | |
| 11 | 2023 | 4 | |
| 12 | 2025 | 3 | |
| 13 | 2025 | 3 | |
| 14 | 2024 | 3 | |
| 15 | 2024 | 3 | |
| 16 | 2023 | 3 | |
| 17 | 2024 | 2 | |
| 18 | 2023 | 2 | |
| 19 | 2023 | 2 | |
| 20 | 2023 | 2 |
About Debendra Muduli
Debendra Muduli is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Neurology and Information Systems, having authored 44 papers that have together received 396 indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (11 papers), Digital Imaging for Blood Diseases (6 papers), AI in cancer detection (6 papers), Retinal Imaging and Analysis (6 papers), Machine Learning and ELM (5 papers), COVID-19 diagnosis using AI (4 papers), Glaucoma and retinal disorders (4 papers) and Face and Expression Recognition (3 papers). The work is most often cited by research in Neurology (109 citations), Artificial Intelligence (250 citations), Radiology, Nuclear Medicine and Imaging (171 citations), Health Information Management (34 citations) and Computer Vision and Pattern Recognition (106 citations). Debendra Muduli has collaborated with scholars based in India, Lebanon and Saudi Arabia. Frequent co-authors include Banshidhar Majhi, Ratnakar Dash, Rakesh Ranjan Kumar, Jitesh Pradhan, Abhinav Kumar, Nikhat Parveen, Santosh Kumar Sharma, Sultan M. Alanazi, Amerah Alabrah and Rojalina Priyadarshini. Their work appears in journals such as IEEE Access, Results in Engineering, Biomedical Signal Processing and Control, Scientific Reports and Array.
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.