Vivek V. Datla
Impact in
- Toxicology top 10%
- Pharmacovigilance and Adverse Drug Reactions
- Artificial Intelligence top 5%
- Topic Modeling
- Machine Learning in Healthcare
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
Papers in
-
- Topic Modeling 15
- Natural Language Processing Techniques 9
- Machine Learning in Healthcare 6
- Advanced Text Analysis Techniques 3
- Intelligent Tutoring Systems and Adaptive Learning 2
- Semantic Web and Ontologies 2
-
- Biomedical Text Mining and Ontologies 9
- Co-authors
- Joey Liu (15 shared papers)Sadid A. Hasan (15 shared papers)Oladimeji Farri (14 shared papers)Ashequl Qadir (14 shared papers)Kathy Lee (13 shared papers)Aaditya Prakash (8 shared papers)Qishi Wu (2 shared papers)Siyuan Zhao (3 shared papers)
- Journals
- Cognitive Science (1 paper)eScholarship (California Digital Library) (1 paper)International Joint Conference on Artificial Intelligence (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)International Conference on Computational Linguistics (1 paper)
- Partner nations
- United StatesFinlandIndia
In The Last Decade
Vivek V. Datla
23 papers receiving 331 citations
Peers
Comparison fields: 5 of 72
- Toxicology 24
- Artificial Intelligence 227
- Health Information Management 20
- Computer Networks and Communications 62
- Information Systems 50
Countries citing papers authored by Vivek V. Datla
This map shows the geographic impact of Vivek V. Datla'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 Vivek V. Datla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vivek V. Datla more than expected).
Fields of papers citing papers by Vivek V. Datla
This network shows the impact of papers produced by Vivek V. Datla. 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 Vivek V. Datla. The network helps show where Vivek V. Datla may publish in the future.
Co-authors
The 25 scholars most cited alongside Vivek V. Datla, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 74 | |
| 2 | 2017 | 56 | |
| 3 | 2010 | 43 | |
| 4 | LIDA: A Computational Model of Global Workspace Theory and Developmental Learning. | 2007 | 32 |
| 5 | 2017 | 22 | |
| 6 | Diagnostic Inferencing via Improving Clinical Concept Extraction with Deep Reinforcement Learning: A Preliminary Study | 2017 | 18 |
| 7 | Neural Clinical Paraphrase Generation with Attention | 2016 | 16 |
| 8 | 2011 | 16 | |
| 9 | Learning to Diagnose: Assimilating Clinical Narratives using Deep Reinforcement Learning | 2017 | 10 |
| 10 | Social Networks are Encoded in Language | 2012 | 10 |
| 11 | 2017 | 10 | |
| 12 | PRNA at ImageCLEF 2017 Caption Prediction and Concept Detection Tasks. | 2017 | 9 |
| 13 | From Head to Toe: Embodiment Through Statistical Linguistic Frequencies | 2012 | 6 |
| 14 | Building an Intelligent PAL from the Tutor.com Session Database Phase 1: Data Mining. | 2014 | 5 |
| 15 | Clinical Question Answering using Key-Value Memory Networks and Knowledge Graph. | 2016 | 5 |
| 16 | Towards Dataset Creation And Establishing Baselines for Sentence-level Neural Clinical Paraphrase Generation and Simplification. | 2018 | 5 |
| 17 | Discourse, Health and Well-Being of Military Populations Through the Social Media Lens. | 2016 | 3 |
| 18 | Open Domain Real-Time Question Answering Based on Semantic and Syntactic Question Similarity. | 2016 | 3 |
| 19 | 2012 | 3 | |
| 20 | A Hybrid Approach to Precision Medicine-related Biomedical Article Retrieval and Clinical Trial Matching. | 2017 | 2 |
About Vivek V. Datla
Vivek V. Datla is a scholar working on Artificial Intelligence, Molecular Biology, Computer Networks and Communications, Social Psychology and Information Systems, having authored 24 papers that have together received 352 indexed citations. Recurring topics across this work include Topic Modeling (15 papers), Natural Language Processing Techniques (9 papers), Biomedical Text Mining and Ontologies (9 papers), Machine Learning in Healthcare (6 papers), Advanced Text Analysis Techniques (3 papers), Multimodal Machine Learning Applications (2 papers), Intelligent Tutoring Systems and Adaptive Learning (2 papers) and Semantic Web and Ontologies (2 papers). The work is most often cited by research in Toxicology (24 citations), Artificial Intelligence (227 citations), Health Information Management (20 citations), Computer Networks and Communications (62 citations) and Information Systems (50 citations). Vivek V. Datla has collaborated with scholars based in United States, Finland and India. Frequent co-authors include Joey Liu, Sadid A. Hasan, Oladimeji Farri, Ashequl Qadir, Kathy Lee, Aaditya Prakash, Qishi Wu, Siyuan Zhao, Sajjan G. Shiva and Sankardas Roy. Their work appears in journals such as Cognitive Science, eScholarship (California Digital Library), International Joint Conference on Artificial Intelligence, Proceedings of the AAAI Conference on Artificial Intelligence and International Conference on Computational Linguistics.
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.