Saptarshi Chatterjee
- Oncology
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Pulmonary and Respiratory Medicine
- Co-authors
- Debangshu DeySugata MunshiArindam MukherjeeKallol PurkaitYan SunXin HuangLü TianShrabanti Chowdhury
- Topics
- Cutaneous Melanoma Detection and Management (9 papers)AI in cancer detection (8 papers)Statistical Methods in Clinical Trials (5 papers)
- Partner nations
- IndiaUnited StatesJapan
In The Last Decade
Saptarshi Chatterjee
32 papers receiving 441 citations
Peers
Comparison fields: 5 of 90
- Oncology 185
- Artificial Intelligence 147
- Radiology, Nuclear Medicine and Imaging 145
- Computer Vision and Pattern Recognition 74
- Pulmonary and Respiratory Medicine 67
Countries citing papers authored by Saptarshi Chatterjee
This map shows the geographic impact of Saptarshi Chatterjee'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 Saptarshi Chatterjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Saptarshi Chatterjee more than expected).
Fields of papers citing papers by Saptarshi Chatterjee
This network shows the impact of papers produced by Saptarshi Chatterjee. 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 Saptarshi Chatterjee. The network helps show where Saptarshi Chatterjee may publish in the future.
Co-authorship network of co-authors of Saptarshi Chatterjee
This figure shows the co-authorship network connecting the top 25 collaborators of Saptarshi Chatterjee. A scholar is included among the top collaborators of Saptarshi Chatterjee 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 Saptarshi Chatterjee. Saptarshi Chatterjee 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 | 12 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 37 | |
| 7 | 21 | |
| 8 | 30 | |
| 9 | 91 | |
| 10 | 3 | |
| 11 | 0 | |
| 12 | 42 | |
| 13 | 8 | |
| 14 | 7 | |
| 15 | 8 | |
| 16 | 34 | |
| 17 | 23 | |
| 18 | MODIFIED MULTI WAY FEEDBACK ENCRYPTION STANDARDVER-2(MWFES-2) | 5 |
| 19 | 22 | |
| 20 | 9 |
About Saptarshi Chatterjee
Saptarshi Chatterjee is a scholar working on Statistics and Probability, Oncology and Computer Vision and Pattern Recognition, having authored 36 papers that have together received 464 indexed citations. Recurring topics across this work include Cutaneous Melanoma Detection and Management (9 papers), AI in cancer detection (8 papers) and Statistical Methods in Clinical Trials (5 papers). The work is most often cited by research in Oncology (185 citations), Radiology, Nuclear Medicine and Imaging (145 citations) and Artificial Intelligence (147 citations). Saptarshi Chatterjee has collaborated with scholars based in India, United States and Japan. Frequent co-authors include Debangshu Dey, Sugata Munshi, Arindam Mukherjee, Kallol Purkait, Yan Sun, Xin Huang, Lü Tian, Shrabanti Chowdhury, Himel Mallick and Viswanath Devanarayan. Their work appears in journals such as Expert Systems with Applications, Statistics in Medicine and Dalton Transactions.
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.