Angshuman Paul
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Biomedical Engineering
- Electrical and Electronic Engineering
- Co-authors
- Dipti Prasad MukherjeeAbhinandan GangopadhyaySaurabh KunduAppa Rao ChinthaPrasun DasD. PatranabisRonald M. SummersThomas C. Shen
- Topics
- AI in cancer detection (11 papers)COVID-19 diagnosis using AI (9 papers)Radiomics and Machine Learning in Medical Imaging (7 papers)
- Journals
- Scientific ReportsIEEE Transactions on Image ProcessingIEEE Transactions on Medical Imaging
- Partner nations
- IndiaUnited StatesSweden
In The Last Decade
Angshuman Paul
35 papers receiving 609 citations
Peers
Comparison fields: 5 of 138
- Artificial Intelligence 241
- Computer Vision and Pattern Recognition 143
- Radiology, Nuclear Medicine and Imaging 141
- Biomedical Engineering 120
- Electrical and Electronic Engineering 103
Countries citing papers authored by Angshuman Paul
This map shows the geographic impact of Angshuman Paul'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 Angshuman Paul with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Angshuman Paul more than expected).
Fields of papers citing papers by Angshuman Paul
This network shows the impact of papers produced by Angshuman Paul. 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 Angshuman Paul. The network helps show where Angshuman Paul may publish in the future.
Co-authorship network of co-authors of Angshuman Paul
This figure shows the co-authorship network connecting the top 25 collaborators of Angshuman Paul. A scholar is included among the top collaborators of Angshuman Paul 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 Angshuman Paul. Angshuman Paul 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 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 7 | |
| 8 | 19 | |
| 9 | 39 | |
| 10 | 8 | |
| 11 | 10 | |
| 12 | 19 | |
| 13 | 12 | |
| 14 | 70 | |
| 15 | 6 | |
| 16 | 5 | |
| 17 | 1 | |
| 18 | 1 | |
| 19 | 5 | |
| 20 | 36 |
About Angshuman Paul
Angshuman Paul is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 39 papers that have together received 648 indexed citations. Recurring topics across this work include AI in cancer detection (11 papers), COVID-19 diagnosis using AI (9 papers) and Radiomics and Machine Learning in Medical Imaging (7 papers). The work is most often cited by research in Health Informatics (14 citations), Artificial Intelligence (241 citations) and Computer Vision and Pattern Recognition (143 citations). Angshuman Paul has collaborated with scholars based in India, United States and Sweden. Frequent co-authors include Dipti Prasad Mukherjee, Abhinandan Gangopadhyay, Saurabh Kundu, Appa Rao Chintha, Prasun Das, D. Patranabis, Ronald M. Summers, Thomas C. Shen, Yuxing Tang and Sungwon Lee. Their work appears in journals such as Scientific Reports, IEEE Transactions on Image Processing and IEEE Transactions on Medical Imaging.
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.