S. Punitha
Impact in
- Artificial Intelligence top 5%
- AI in cancer detection
- Metaheuristic Optimization Algorithms Research
-
- Artificial Intelligence in Healthcare
Papers in
-
- AI in cancer detection 6
- Advanced Clustering Algorithms Research 4
- Semantic Web and Ontologies 3
- Text and Document Classification Technologies 3
- Co-authors
- Thompson StephanA. AmuthanK. Suresh JosephFadi Al‐TurjmanS. RaviM. PunithavalliRamani KannanAjith Abraham
- Journals
- IEEE Access (2 papers)Journal of Intelligent & Fuzzy Systems (1 paper)International Journal of Fuzzy Systems (1 paper)Neural Computing and Applications (1 paper)Sustainability (1 paper)
- Partner nations
- IndiaMalaysiaUnited States
In The Last Decade
S. Punitha
34 papers receiving 468 citations
Peers
Comparison fields: 5 of 98
- Artificial Intelligence 321
- Health Information Management 42
- Neurology 72
- Radiology, Nuclear Medicine and Imaging 146
- Computer Vision and Pattern Recognition 103
Countries citing papers authored by S. Punitha
This map shows the geographic impact of S. Punitha'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 S. Punitha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Punitha more than expected).
Fields of papers citing papers by S. Punitha
This network shows the impact of papers produced by S. Punitha. 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 S. Punitha. The network helps show where S. Punitha may publish in the future.
Co-authorship network
The 25 scholars most cited alongside S. Punitha, 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 | 2024 | 6 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 4 | |
| 4 | 2024 | 7 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 0 | |
| 7 | 2023 | 6 | |
| 8 | 2022 | 10 | |
| 9 | 2021 | 43 | |
| 10 | 2021 | 9 | |
| 11 | 2020 | 6 | |
| 12 | 2020 | 2 | |
| 13 | 2020 | 28 | |
| 14 | 2019 | 29 | |
| 15 | 2019 | 1 | |
| 16 | 2018 | 83 | |
| 17 | 2013 | 5 | |
| 18 | 2013 | 0 | |
| 19 | 2011 | 0 | |
| 20 | Document Clustering using Linear Partitioning and Reallocation using EM Algorithm | 2010 | 1 |
About S. Punitha
S. Punitha is a scholar working on Health Informatics, Artificial Intelligence, Computer Vision and Pattern Recognition, Neurology and Health Information Management, having authored 42 papers that have together received 494 indexed citations. Recurring topics across this work include AI in cancer detection (6 papers), Advanced Clustering Algorithms Research (4 papers), Stock Market Forecasting Methods (4 papers), Brain Tumor Detection and Classification (4 papers), Data Mining Algorithms and Applications (3 papers), Face and Expression Recognition (3 papers), Semantic Web and Ontologies (3 papers) and Text and Document Classification Technologies (3 papers). The work is most often cited by research in Artificial Intelligence (321 citations), Health Information Management (42 citations), Neurology (72 citations), Radiology, Nuclear Medicine and Imaging (146 citations) and Computer Vision and Pattern Recognition (103 citations). S. Punitha has collaborated with scholars based in India, Malaysia and United States. Frequent co-authors include Thompson Stephan, A. Amuthan, K. Suresh Joseph, Fadi Al‐Turjman, S. Ravi, M. Punithavalli, Ramani Kannan, Ajith Abraham, Mufti Mahmud and M. Shamim Kaiser. Their work appears in journals such as IEEE Access, Journal of Intelligent & Fuzzy Systems, International Journal of Fuzzy Systems, Neural Computing and Applications and Sustainability.
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.