Nitesh Pradhan
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging
- Computer Vision and Pattern Recognition
- Biomedical Engineering
- Neurology
- Co-authors
- Vijaypal Singh DhakaGeeta RaniManasi GyanchandaniRajesh WadhvaniHimanshu ChaudharyDeepak SinwarJoel J. P. C. RodriguesSahil Verma
- Topics
- AI in cancer detection (9 papers)Radiomics and Machine Learning in Medical Imaging (5 papers)Artificial Intelligence in Healthcare (5 papers)
In The Last Decade
Nitesh Pradhan
18 papers receiving 216 citations
Peers
Comparison fields: 5 of 78
- Artificial Intelligence 107
- Radiology, Nuclear Medicine and Imaging 62
- Computer Vision and Pattern Recognition 44
- Biomedical Engineering 36
- Neurology 16
Countries citing papers authored by Nitesh Pradhan
This map shows the geographic impact of Nitesh Pradhan'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 Nitesh Pradhan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nitesh Pradhan more than expected).
Fields of papers citing papers by Nitesh Pradhan
This network shows the impact of papers produced by Nitesh Pradhan. 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 Nitesh Pradhan. The network helps show where Nitesh Pradhan may publish in the future.
Co-authorship network of co-authors of Nitesh Pradhan
This figure shows the co-authorship network connecting the top 25 collaborators of Nitesh Pradhan. A scholar is included among the top collaborators of Nitesh Pradhan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nitesh Pradhan. Nitesh Pradhan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 9 | |
| 3 | 1 | |
| 4 | 11 | |
| 5 | 6 | |
| 6 | 18 | |
| 7 | 12 | |
| 8 | 17 | |
| 9 | PHACOEMULSIFICATION VERSUS SMALL INCISION CATARACT SURGERY -A SURGICAL OPTION FOR IMMATURE CATARACT IN DEVELOPING COUNTRIES | 0 |
| 10 | 24 | |
| 11 | 13 | |
| 12 | 0 | |
| 13 | 22 | |
| 14 | 1 | |
| 15 | 7 | |
| 16 | 0 | |
| 17 | 4 | |
| 18 | 37 | |
| 19 | Development of Algorithm for High Resolution Retinex for Image Enhancement | 0 |
| 20 | SIMULATION RESULTS FOR WAVELET APPROXIMATION | 1 |
About Nitesh Pradhan
Nitesh Pradhan is a scholar working on Health Information Management, Health Informatics and Artificial Intelligence, having authored 24 papers that have together received 223 indexed citations. Recurring topics across this work include AI in cancer detection (9 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Artificial Intelligence in Healthcare (5 papers). The work is most often cited by research in Health Informatics (10 citations), Artificial Intelligence (107 citations) and Health Information Management (13 citations). Nitesh Pradhan has collaborated with scholars based in India, Ecuador and Portugal. Frequent co-authors include Vijaypal Singh Dhaka, Geeta Rani, Manasi Gyanchandani, Rajesh Wadhvani, Himanshu Chaudhary, Deepak Sinwar, Joel J. P. C. Rodrigues, Sahil Verma, Saumya Pandey and Geeta Rani. Their work appears in journals such as IEEE Access, Applied Soft Computing and Neural Computing and Applications.
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.