B. Nithya
Impact in
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- Artificial Intelligence in Healthcare
- Artificial Intelligence top 10%
- AI in cancer detection
- Imbalanced Data Classification Techniques
- Machine Learning in Healthcare
- Topic Modeling
Papers in
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- Imbalanced Data Classification Techniques 3
- Quantum Information and Cryptography 2
- Quantum Computing Algorithms and Architecture 2
- AI in cancer detection 2
- Natural Language Processing Techniques 1
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- Artificial Intelligence in Healthcare 4
- Journals
- International Journal of Knowledge-based and Intelligent Engineering Systems (1 paper)SN Applied Sciences (1 paper)International Journal of Advanced Computer Science and Applications (1 paper)International Journal of Computer Applications (1 paper)2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS) (1 paper)
In The Last Decade
B. Nithya
10 papers receiving 200 citations
Peers
Comparison fields: 5 of 79
- Health Information Management 101
- Artificial Intelligence 135
- Health Informatics 4
- Computer Vision and Pattern Recognition 31
- Radiology, Nuclear Medicine and Imaging 35
Countries citing papers authored by B. Nithya
This map shows the geographic impact of B. Nithya'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 B. Nithya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites B. Nithya more than expected).
Fields of papers citing papers by B. Nithya
This network shows the impact of papers produced by B. Nithya. 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 B. Nithya. The network helps show where B. Nithya may publish in the future.
Co-authors
The 3 scholars most cited alongside B. Nithya, 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 | 2017 | 122 | |
| 2 | 2019 | 82 | |
| 3 | 2013 | 11 | |
| 4 | 2022 | 11 | |
| 5 | 2020 | 7 | |
| 6 | Cryptographic System Models and Algorithms for Network Security | 2019 | 3 |
| 7 | 2016 | 3 | |
| 8 | 2022 | 3 | |
| 9 | 2020 | 2 | |
| 10 | 2022 | 2 | |
| 11 | 2024 | 1 | |
| 12 | 2024 | 0 | |
| 13 | 2023 | 0 |
About B. Nithya
B. Nithya is a scholar working on Artificial Intelligence, Health Information Management, Information Systems, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 13 papers that have together received 247 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (4 papers), Imbalanced Data Classification Techniques (3 papers), Quantum Information and Cryptography (2 papers), Quantum Computing Algorithms and Architecture (2 papers), Data Mining Algorithms and Applications (2 papers), AI in cancer detection (2 papers), Natural Language Processing Techniques (1 paper) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Health Information Management (101 citations), Artificial Intelligence (135 citations), Health Informatics (4 citations), Computer Vision and Pattern Recognition (31 citations) and Radiology, Nuclear Medicine and Imaging (35 citations). B. Nithya has collaborated with scholars based in India and Canada. Frequent co-authors include V. Ilango, S. Mohan Kumar and Vikash Kumar. Their work appears in journals such as International Journal of Knowledge-based and Intelligent Engineering Systems, SN Applied Sciences, International Journal of Advanced Computer Science and Applications, International Journal of Computer Applications and 2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS).
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.