Prakash Choudhary
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 5%
- Health Information Management top 2%
- Neurology top 10%
- Co-authors
- Tarun AgrawalAbhishek HazraNeeta NainKh. Manglem SinghPrabhishek SinghManoj DiwakarMainak AdhikariAchyut Shankar
- Topics
- Handwritten Text Recognition Techniques (13 papers)COVID-19 diagnosis using AI (11 papers)Radiomics and Machine Learning in Medical Imaging (8 papers)
- Partner nations
- IndiaEstoniaUnited Kingdom
In The Last Decade
Prakash Choudhary
39 papers receiving 487 citations
Peers
Comparison fields: 5 of 84
- Artificial Intelligence 188
- Radiology, Nuclear Medicine and Imaging 170
- Computer Vision and Pattern Recognition 169
- Health Information Management 76
- Neurology 73
Countries citing papers authored by Prakash Choudhary
This map shows the geographic impact of Prakash Choudhary'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 Prakash Choudhary with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prakash Choudhary more than expected).
Fields of papers citing papers by Prakash Choudhary
This network shows the impact of papers produced by Prakash Choudhary. 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 Prakash Choudhary. The network helps show where Prakash Choudhary may publish in the future.
Co-authorship network of co-authors of Prakash Choudhary
This figure shows the co-authorship network connecting the top 25 collaborators of Prakash Choudhary. A scholar is included among the top collaborators of Prakash Choudhary 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 Prakash Choudhary. Prakash Choudhary is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 8 | |
| 5 | 13 | |
| 6 | 0 | |
| 7 | 28 | |
| 8 | 6 | |
| 9 | 2 | |
| 10 | 9 | |
| 11 | 9 | |
| 12 | 10 | |
| 13 | 1 | |
| 14 | 55 | |
| 15 | 55 | |
| 16 | 4 | |
| 17 | 4 | |
| 18 | 9 | |
| 19 | 1 | |
| 20 | 4 |
About Prakash Choudhary
Prakash Choudhary is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Neurology, having authored 45 papers that have together received 512 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (13 papers), COVID-19 diagnosis using AI (11 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). The work is most often cited by research in Health Information Management (76 citations), Neurology (73 citations) and Computer Vision and Pattern Recognition (169 citations). Prakash Choudhary has collaborated with scholars based in India, Estonia and United Kingdom. Frequent co-authors include Tarun Agrawal, Abhishek Hazra, Neeta Nain, Kh. Manglem Singh, Prabhishek Singh, Manoj Diwakar, Mainak Adhikari, Achyut Shankar, Sachin Jadhav and Virendra Gajbhiye. Their work appears in journals such as Scientific Reports, International Journal of Pharmaceutics and Human Reproduction.
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.