D. Ravindran
Impact in
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- Artificial Intelligence in Healthcare
Papers in
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- IoT and Edge/Fog Computing 7
- Caching and Content Delivery 1
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- Cloud Computing and Resource Management 4
- Blockchain Technology Applications and Security 2
- Co-authors
- Kathiravan Srinivasan (3 shared papers)P. M. Durai Raj Vincent (3 shared papers)Daniel Gutiérrez Reina (1 shared paper)Yuh‐Chung Hu (1 shared paper)Susan Gauch (1 shared paper)Chuan‐Yu Chang (1 shared paper)E. Kirubakaran (1 shared paper)M Ramachandran (1 shared paper)
- Journals
- Electronics (1 paper)Sensors (1 paper)Journal of Intelligent Systems (1 paper)Diagnostics (1 paper)Baghdad Science Journal (2 papers)
- Partner nations
- IndiaUnited StatesTaiwan
In The Last Decade
D. Ravindran
14 papers receiving 258 citations
D. Ravindran's Hit Papers
Peers
Comparison fields: 5 of 51
- Health Information Management 81
- Health Informatics 9
- Computer Networks and Communications 125
- Information Systems 91
- Medical Laboratory Technology 3
Countries citing papers authored by D. Ravindran
This map shows the geographic impact of D. Ravindran'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 D. Ravindran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. Ravindran more than expected).
Fields of papers citing papers by D. Ravindran
This network shows the impact of papers produced by D. Ravindran. 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 D. Ravindran. The network helps show where D. Ravindran may publish in the future.
Co-authors
The 9 scholars most cited alongside D. Ravindran, 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 | IoT-Cloud-Based Smart Healthcare Monitoring System for Heart Disease Prediction via Deep Learning Hit paper breakdown → | 2022 | 136 |
| 2 | 2021 | 81 | |
| 3 | 2023 | 10 | |
| 4 | 2019 | 10 | |
| 5 | 2022 | 9 | |
| 6 | 2020 | 9 | |
| 7 | 2017 | 7 | |
| 8 | 2010 | 5 | |
| 9 | 2017 | 4 | |
| 10 | Fog Computing Resource Optimization: A Review on Current Scenarios and Resource Management | 2019 | 3 |
| 11 | Technical Review Of Apache Flink For Big Data | 2021 | 3 |
| 12 | 2016 | 2 | |
| 13 | 2017 | 2 | |
| 14 | 2023 | 1 |
About D. Ravindran
D. Ravindran is a scholar working on Computer Networks and Communications, Information Systems, Health Information Management, Artificial Intelligence and Information Systems and Management, having authored 14 papers that have together received 282 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (7 papers), Cloud Computing and Resource Management (4 papers), Artificial Intelligence in Healthcare (2 papers), Blockchain Technology Applications and Security (2 papers), Advanced Text Analysis Techniques (1 paper), Semantic Web and Ontologies (1 paper), IoT Networks and Protocols (1 paper) and Caching and Content Delivery (1 paper). The work is most often cited by research in Health Information Management (81 citations), Health Informatics (9 citations), Computer Networks and Communications (125 citations), Information Systems (91 citations) and Medical Laboratory Technology (3 citations). D. Ravindran has collaborated with scholars based in India, United States and Taiwan. Frequent co-authors include Kathiravan Srinivasan, P. M. Durai Raj Vincent, Daniel Gutiérrez Reina, Yuh‐Chung Hu, Susan Gauch, Chuan‐Yu Chang, E. Kirubakaran, M Ramachandran and Vimala Saravanan. Their work appears in journals such as Electronics, Sensors, Journal of Intelligent Systems, Diagnostics and Baghdad Science Journal.
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.