Vipula Rawte
Impact in
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- Artificial Intelligence in Healthcare and Education
- Health Information Management top 10%
- Artificial Intelligence in Healthcare
Papers in
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- Topic Modeling 3
- Semantic Web and Ontologies 2
- Machine Learning in Healthcare 2
- Anomaly Detection Techniques and Applications 2
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- Stock Market Forecasting Methods 4
- Co-authors
- G. Anuradha (1 shared paper)Amit Sheth (2 shared papers)Amitava Das (1 shared paper)Aman Chadha (2 shared papers)Swagata Chakraborty (1 shared paper)Aparna Gupta (4 shared papers)Mohammed J. Zaki (4 shared papers)Manas Gaur (1 shared paper)
- Journals
- Frontiers in Big Data (1 paper)Computational Economics (1 paper)ACM Transactions on Knowledge Discovery from Data (1 paper)International Journal of Engineering Research and (1 paper)
- Partner nations
- United StatesBangladeshIndia
In The Last Decade
Vipula Rawte
8 papers receiving 114 citations
Peers
Comparison fields: 5 of 58
- Health Informatics 11
- Health Information Management 25
- Artificial Intelligence 78
- Applied Psychology 7
- Accounting 9
Countries citing papers authored by Vipula Rawte
This map shows the geographic impact of Vipula Rawte'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 Vipula Rawte with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vipula Rawte more than expected).
Fields of papers citing papers by Vipula Rawte
This network shows the impact of papers produced by Vipula Rawte. 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 Vipula Rawte. The network helps show where Vipula Rawte may publish in the future.
Co-authors
The 16 scholars most cited alongside Vipula Rawte, 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 | 2015 | 58 | |
| 2 | 2023 | 38 | |
| 3 | 2023 | 13 | |
| 4 | 2015 | 6 | |
| 5 | 2018 | 4 | |
| 6 | 2015 | 4 | |
| 7 | 2023 | 3 | |
| 8 | 2025 | 2 | |
| 9 | 2024 | 1 | |
| 10 | 2025 | 0 | |
| 11 | 2017 | 0 | |
| 12 | 2018 | 0 |
About Vipula Rawte
Vipula Rawte is a scholar working on Artificial Intelligence, Management Science and Operations Research, Social Psychology, Health Information Management and Accounting, having authored 12 papers that have together received 129 indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (4 papers), Topic Modeling (3 papers), Semantic Web and Ontologies (2 papers), Artificial Intelligence in Healthcare (2 papers), Mental Health via Writing (2 papers), Financial Distress and Bankruptcy Prediction (2 papers), Machine Learning in Healthcare (2 papers) and Anomaly Detection Techniques and Applications (2 papers). The work is most often cited by research in Health Informatics (11 citations), Health Information Management (25 citations), Artificial Intelligence (78 citations), Applied Psychology (7 citations) and Accounting (9 citations). Vipula Rawte has collaborated with scholars based in United States, Bangladesh and India. Frequent co-authors include G. Anuradha, Amit Sheth, Amitava Das, Aman Chadha, Swagata Chakraborty, Aparna Gupta, Mohammed J. Zaki, Manas Gaur, Ashwin Kalyan and Kaushik Roy. Their work appears in journals such as Frontiers in Big Data, Computational Economics, ACM Transactions on Knowledge Discovery from Data and International Journal of Engineering Research and.
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.