Sumit Das
Impact in
- Health Informatics top 10%
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- Artificial Intelligence in Healthcare
Papers in
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- Artificial Intelligence in Healthcare 6
-
- AI in cancer detection 3
- Co-authors
- Aritra Dey (3 shared papers)Akash Pal (1 shared paper)Nabamita Banerjee Roy (1 shared paper)Spenta R. Wadia (2 shared papers)Manas Kumar Sanyal (9 shared papers)Suman Biswas (1 shared paper)Anupam Basu (2 shared papers)Antal Jevicki (1 shared paper)
- Journals
- Proceedings of the National Academy of Sciences (1 paper)Clinical Neuropathology (1 paper)Journal of High Energy Physics (1 paper)Indian Journal of Science and Technology (1 paper)Modern Physics Letters A (2 papers)
- Partner nations
- IndiaUnited States
In The Last Decade
Sumit Das
31 papers receiving 535 citations
Sumit Das's Hit Papers
Peers
Comparison fields: 5 of 138
- Health Informatics 25
- Health Information Management 39
- Complementary and alternative medicine 49
- Nuclear and High Energy Physics 68
- Artificial Intelligence 118
Countries citing papers authored by Sumit Das
This map shows the geographic impact of Sumit Das'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 Sumit Das with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sumit Das more than expected).
Fields of papers citing papers by Sumit Das
This network shows the impact of papers produced by Sumit Das. 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 Sumit Das. The network helps show where Sumit Das may publish in the future.
Co-authors
The 17 scholars most cited alongside Sumit Das, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Applications of Artificial Intelligence in Machine Learning: Review and Prospect Hit paper breakdown → | 2015 | 247 |
| 2 | 2010 | 131 | |
| 3 | 1989 | 65 | |
| 4 | 2017 | 31 | |
| 5 | 2018 | 10 | |
| 6 | 2019 | 8 | |
| 7 | 2019 | 8 | |
| 8 | 2022 | 6 | |
| 9 | 2018 | 6 | |
| 10 | 1990 | 5 | |
| 11 | 2010 | 4 | |
| 12 | 2023 | 4 | |
| 13 | 2021 | 4 | |
| 14 | 2019 | 3 | |
| 15 | 2024 | 3 | |
| 16 | 2023 | 3 | |
| 17 | 2021 | 3 | |
| 18 | 2010 | 2 | |
| 19 | 2024 | 2 | |
| 20 | 2023 | 2 |
About Sumit Das
Sumit Das is a scholar working on Health Information Management, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Neurology and Media Technology, having authored 34 papers that have together received 564 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (6 papers), COVID-19 diagnosis using AI (3 papers), AI in cancer detection (3 papers), Brain Tumor Detection and Classification (2 papers), Musculoskeletal pain and rehabilitation (2 papers), Engineering Education and Curriculum Development (2 papers), Spam and Phishing Detection (2 papers) and Infrared Thermography in Medicine (2 papers). The work is most often cited by research in Health Informatics (25 citations), Health Information Management (39 citations), Complementary and alternative medicine (49 citations), Nuclear and High Energy Physics (68 citations) and Artificial Intelligence (118 citations). Sumit Das has collaborated with scholars based in India and United States. Frequent co-authors include Aritra Dey, Akash Pal, Nabamita Banerjee Roy, Spenta R. Wadia, Manas Kumar Sanyal, Suman Biswas, Anupam Basu, Antal Jevicki, Soumyajit Dey and Anirvan M. Sengupta. Their work appears in journals such as Proceedings of the National Academy of Sciences, Clinical Neuropathology, Journal of High Energy Physics, Indian Journal of Science and Technology and Modern Physics Letters A.
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.