B Divya
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 10%
- Artificial Intelligence Applications
- Multi-Agent Systems and Negotiation
- Explainable Artificial Intelligence (XAI)
- AI-based Problem Solving and Planning
Papers in
-
- Brain Tumor Detection and Classification 3
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- Artificial Intelligence Applications 2
- Psychiatry, Mental Health, Neuroscience 1
- AI-based Problem Solving and Planning 1
- Co-authors
- Deepak Bhaskar Acharya (4 shared papers)Koteshwara Prakashini (4 shared papers)Pitchaiah Mandava (3 shared papers)Rajesh Parameshwaran Nair (4 shared papers)Deepu Vijayasenan (3 shared papers)Girish R. Menon (3 shared papers)
- Journals
- IEEE Access (3 papers)F1000Research (1 paper)Biomedical Signal Processing and Control (1 paper)Lecture notes in networks and systems (1 paper)ACM Southeast Conference (ACMSE) (1 paper)
- Partner nations
- IndiaUnited States
In The Last Decade
B Divya
11 papers receiving 313 citations
B Divya's Hit Papers
Peers
Comparison fields: 5 of 76
- Health Informatics 25
- Artificial Intelligence 128
- Safety Research 40
- Information Systems 50
- Industrial and Manufacturing Engineering 17
Countries citing papers authored by B Divya
This map shows the geographic impact of B Divya'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 Divya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites B Divya more than expected).
Fields of papers citing papers by B Divya
This network shows the impact of papers produced by B Divya. 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 Divya. The network helps show where B Divya may publish in the future.
Co-authors
The 6 scholars most cited alongside B Divya, 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 | Agentic AI: Autonomous Intelligence for Complex Goals—A Comprehensive Survey Hit paper breakdown → | 2025 | 289 |
| 2 | 2024 | 16 | |
| 3 | 2021 | 10 | |
| 4 | 2024 | 10 | |
| 5 | 2025 | 4 | |
| 6 | 2023 | 3 | |
| 7 | 2023 | 3 | |
| 8 | 2024 | 2 | |
| 9 | 2024 | 2 | |
| 10 | 2025 | 2 | |
| 11 | 2024 | 1 | |
| 12 | 2025 | 0 |
About B Divya
B Divya is a scholar working on Neurology, Artificial Intelligence, Oncology, Health Information Management and Management Science and Operations Research, having authored 12 papers that have together received 342 indexed citations. Recurring topics across this work include Brain Tumor Detection and Classification (3 papers), Artificial Intelligence Applications (2 papers), Cutaneous Melanoma Detection and Management (1 paper), Psychiatry, Mental Health, Neuroscience (1 paper), Sepsis Diagnosis and Treatment (1 paper), AI-based Problem Solving and Planning (1 paper), Stock Market Forecasting Methods (1 paper) and Artificial Intelligence in Healthcare (1 paper). The work is most often cited by research in Health Informatics (25 citations), Artificial Intelligence (128 citations), Safety Research (40 citations), Information Systems (50 citations) and Industrial and Manufacturing Engineering (17 citations). B Divya has collaborated with scholars based in India and United States. Frequent co-authors include Deepak Bhaskar Acharya, Koteshwara Prakashini, Pitchaiah Mandava, Rajesh Parameshwaran Nair, Deepu Vijayasenan and Girish R. Menon. Their work appears in journals such as IEEE Access, F1000Research, Biomedical Signal Processing and Control, Lecture notes in networks and systems and ACM Southeast Conference (ACMSE).
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.