Satya Ranjan Dash
- Artificial Intelligence top 10%
- Management Science and Operations Research top 10%
- Cognitive Neuroscience
- Information Systems
- Computational Theory and Mathematics
- Co-authors
- Sujit DasAzian Azamimi AbdullahShantipriya ParidaRoman R. PoznańskiSatchidananda DehuriP.K. DashA.C. LiewAmit Patra
- Topics
- Natural Language Processing Techniques (9 papers)Topic Modeling (8 papers)Artificial Intelligence in Healthcare (7 papers)
- Cited by
- Management Science and Operations ResearchHealth Information ManagementArtificial Intelligence
- Journals
- GastroenterologyEngineering Applications of Artificial IntelligenceLanguage Resources and Evaluation
- Partner nations
- IndiaUnited StatesMalaysia
In The Last Decade
Satya Ranjan Dash
42 papers receiving 339 citations
Peers
Comparison fields: 5 of 94
- Artificial Intelligence 116
- Management Science and Operations Research 81
- Cognitive Neuroscience 62
- Information Systems 40
- Computational Theory and Mathematics 35
Countries citing papers authored by Satya Ranjan Dash
This map shows the geographic impact of Satya Ranjan Dash'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 Satya Ranjan Dash with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Satya Ranjan Dash more than expected).
Fields of papers citing papers by Satya Ranjan Dash
This network shows the impact of papers produced by Satya Ranjan Dash. 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 Satya Ranjan Dash. The network helps show where Satya Ranjan Dash may publish in the future.
Co-authorship network of co-authors of Satya Ranjan Dash
This figure shows the co-authorship network connecting the top 25 collaborators of Satya Ranjan Dash. A scholar is included among the top collaborators of Satya Ranjan Dash 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 Satya Ranjan Dash. Satya Ranjan Dash is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 5 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 2 | |
| 9 | 0 | |
| 10 | 0 | |
| 11 | 0 | |
| 12 | 1 | |
| 13 | 15 | |
| 14 | 4 | |
| 15 | 94 | |
| 16 | 4 | |
| 17 | 2 | |
| 18 | 5 | |
| 19 | 3 | |
| 20 | Comparative Study of Different ClassificationTechniques for Post Operative Patient Dataset | 3 |
About Satya Ranjan Dash
Satya Ranjan Dash is a scholar working on Health Information Management, Artificial Intelligence and Health Informatics, having authored 57 papers that have together received 361 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (9 papers), Topic Modeling (8 papers) and Artificial Intelligence in Healthcare (7 papers). The work is most often cited by research in Management Science and Operations Research (81 citations), Health Information Management (25 citations) and Artificial Intelligence (116 citations). Satya Ranjan Dash has collaborated with scholars based in India, United States and Malaysia. Frequent co-authors include Sujit Das, Azian Azamimi Abdullah, Shantipriya Parida, Roman R. Poznański, Satchidananda Dehuri, P.K. Dash, A.C. Liew, Amit Patra, Palash Dutta and Ondřej Bojar. Their work appears in journals such as Gastroenterology, Engineering Applications of Artificial Intelligence and Language Resources and Evaluation.
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.