Monjoy Saha
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Biophysics top 5%
- Cell Image Analysis Techniques
Papers in
-
- AI in cancer detection 9
- Machine Learning in Healthcare 2
-
- Radiomics and Machine Learning in Medical Imaging 6
- Co-authors
- Chandan Chakraborty (8 shared papers)Daniel Racoceanu (1 shared paper)Indu Arun (5 shared papers)Sanjoy Chatterjee (5 shared papers)Rosina Ahmed (4 shared papers)Rashmi Mukherjee (2 shared papers)Muhammad Naeem (1 shared paper)Aurobinda Routray (1 shared paper)
- Journals
- Scientific Reports (2 papers)Tissue and Cell (2 papers)PLoS ONE (1 paper)IEEE Transactions on Image Processing (1 paper)Journal of Microscopy (1 paper)
- Partner nations
- United StatesIndiaFrance
In The Last Decade
Monjoy Saha
18 papers receiving 560 citations
Peers
Comparison fields: 5 of 91
- Health Informatics 22
- Biophysics 81
- Radiology, Nuclear Medicine and Imaging 238
- Artificial Intelligence 361
- Computer Vision and Pattern Recognition 163
Countries citing papers authored by Monjoy Saha
This map shows the geographic impact of Monjoy Saha'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 Monjoy Saha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Monjoy Saha more than expected).
Fields of papers citing papers by Monjoy Saha
This network shows the impact of papers produced by Monjoy Saha. 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 Monjoy Saha. The network helps show where Monjoy Saha may publish in the future.
Co-authors
The 25 scholars most cited alongside Monjoy Saha, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 149 | |
| 2 | 2018 | 136 | |
| 3 | 2017 | 84 | |
| 4 | 2022 | 39 | |
| 5 | 2016 | 38 | |
| 6 | 2015 | 26 | |
| 7 | 2020 | 24 | |
| 8 | 2022 | 17 | |
| 9 | 2021 | 11 | |
| 10 | 2022 | 10 | |
| 11 | 2023 | 9 | |
| 12 | 2017 | 7 | |
| 13 | 2016 | 7 | |
| 14 | 2023 | 7 | |
| 15 | 2024 | 6 | |
| 16 | 2017 | 4 | |
| 17 | 2022 | 3 | |
| 18 | 2024 | 2 | |
| 19 | 2025 | 0 |
About Monjoy Saha
Monjoy Saha is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Molecular Biology and Biophysics, having authored 19 papers that have together received 579 indexed citations. Recurring topics across this work include AI in cancer detection (9 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Cell Image Analysis Techniques (4 papers), Gene expression and cancer classification (3 papers), Image Retrieval and Classification Techniques (3 papers), Advanced Radiotherapy Techniques (2 papers), Digital Imaging for Blood Diseases (2 papers) and Machine Learning in Healthcare (2 papers). The work is most often cited by research in Health Informatics (22 citations), Biophysics (81 citations), Radiology, Nuclear Medicine and Imaging (238 citations), Artificial Intelligence (361 citations) and Computer Vision and Pattern Recognition (163 citations). Monjoy Saha has collaborated with scholars based in United States, India and France. Frequent co-authors include Chandan Chakraborty, Daniel Racoceanu, Indu Arun, Sanjoy Chatterjee, Rosina Ahmed, Rashmi Mukherjee, Muhammad Naeem, Aurobinda Routray, Ashish Sharma and Imon Banerjee. Their work appears in journals such as Scientific Reports, Tissue and Cell, PLoS ONE, IEEE Transactions on Image Processing and Journal of Microscopy.
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.