Sunil Kumar Sahu

603 citations
12 papers · 280 · h-index 7

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Advanced Text Analysis Techniques
    • Advanced Graph Neural Networks
    • Text and Document Classification Technologies
    • Sentiment Analysis and Opinion Mining

Papers in

    • Topic Modeling 5
    • Natural Language Processing Techniques 4
    • Imbalanced Data Classification Techniques 1
    • Fuzzy Logic and Control Systems 1
    • Biomedical Text Mining and Ontologies 3

Sunil Kumar Sahu

11 papers receiving 272 citations

Peers

Sunil Kumar Sahu
Comparison fields: 5 of 45
  • Artificial Intelligence 199
  • Health Information Management 10
  • Management Science and Operations Research 18
  • Molecular Biology 69
  • Health Informatics 1
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Citations per field
00.5×8.6×
Kevin Livingston · 1×
Citations per year

Countries citing papers authored by Sunil Kumar Sahu

Since Specialization
Citations

This map shows the geographic impact of Sunil Kumar Sahu'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 Sunil Kumar Sahu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sunil Kumar Sahu more than expected).

Fields of papers citing papers by Sunil Kumar Sahu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sunil Kumar Sahu. 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 Sunil Kumar Sahu. The network helps show where Sunil Kumar Sahu may publish in the future.

Co-authors

The 15 scholars most cited alongside Sunil Kumar Sahu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sunil Kumar Sahu Line = papers co-authored together Sunil Kumar Sahu links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2019142
2 201553
3 201723
4 201615
5 202014
6 202114
7 20226
8
Performance Analysis of Symmetric Encryption Algorithms for Mobile ad hoc Network
20146
9 20233
10 20202
11
Fuzzy Logic based Soft Filters for Removing Noise and Preserving Edge
20182
12 20240

About Sunil Kumar Sahu

Sunil Kumar Sahu is a scholar working on Artificial Intelligence, Molecular Biology, Health Information Management, Radiology, Nuclear Medicine and Imaging and Electrical and Electronic Engineering, having authored 12 papers that have together received 280 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Natural Language Processing Techniques (4 papers), Biomedical Text Mining and Ontologies (3 papers), Artificial Intelligence in Healthcare (2 papers), Imbalanced Data Classification Techniques (1 paper), Chaos-based Image/Signal Encryption (1 paper), Patient Satisfaction in Healthcare (1 paper) and Fuzzy Logic and Control Systems (1 paper). The work is most often cited by research in Artificial Intelligence (199 citations), Health Information Management (10 citations), Management Science and Operations Research (18 citations), Molecular Biology (69 citations) and Health Informatics (1 citation). Sunil Kumar Sahu has collaborated with scholars based in India, United Arab Emirates and Japan. Frequent co-authors include Makoto Miwa, Ashish Anand, Desh Raj, Samarth Tripathi, Billy Chiu, Ajay Singh, K.P. Muthe, Shovit Bhattacharya, Ravi Verma and Mukesh Prasad. Their work appears in journals such as IEEE Transactions on Industrial Electronics, Applied Sciences, International Journal of Machine Learning and Computing, Journal of Physics Conference Series and Journal of Applied Spectroscopy.

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.

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