Vivek V. Datla

1.0k citations
26 papers · 422 · h-index 12

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Machine Learning in Healthcare
    • Advanced Text Analysis Techniques
  • Toxicology top 10%
    • Pharmacovigilance and Adverse Drug Reactions

Papers in

    • Topic Modeling 16
    • Natural Language Processing Techniques 9
    • Machine Learning in Healthcare 6
    • Advanced Text Analysis Techniques 3
    • Intelligent Tutoring Systems and Adaptive Learning 2
    • Biomedical Text Mining and Ontologies 10

Vivek V. Datla

25 papers receiving 398 citations

Peers

Vivek V. Datla
Comparison fields: 5 of 73
  • Artificial Intelligence 270
  • Toxicology 25
  • Health Information Management 21
  • Computer Networks and Communications 76
  • Information Systems 63
Replace Shaowu Zhang with:
Shaowu Zhang China
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Sherine Rady Egypt
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Chaoqi Yang United States
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Citations per field
00.5×8.4×
Shaowu Zhang · 1×
Citations per year

Countries citing papers authored by Vivek V. Datla

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Vivek V. Datla Line = papers co-authored together Vivek V. Datla links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201780
2 201760
3 201056
4
LIDA: A Computational Model of Global Workspace Theory and Developmental Learning.
200735
5 201725
6
Diagnostic Inferencing via Improving Clinical Concept Extraction with Deep Reinforcement Learning: A Preliminary Study
201722
7
Neural Clinical Paraphrase Generation with Attention
201619
8 201119
9
Learning to Diagnose: Assimilating Clinical Narratives using Deep Reinforcement Learning
201714
10 201713
11
Social Networks are Encoded in Language
201212
12 201811
13
PRNA at ImageCLEF 2017 Caption Prediction and Concept Detection Tasks.
201710
14
Building an Intelligent PAL from the Tutor.com Session Database Phase 1: Data Mining.
20149
15
Towards Dataset Creation And Establishing Baselines for Sentence-level Neural Clinical Paraphrase Generation and Simplification.
20187
16
From Head to Toe: Embodiment Through Statistical Linguistic Frequencies
20126
17
Clinical Question Answering using Key-Value Memory Networks and Knowledge Graph.
20165
18 20124
19
A Hybrid Approach to Precision Medicine-related Biomedical Article Retrieval and Clinical Trial Matching.
20173
20
Discourse, Health and Well-Being of Military Populations Through the Social Media Lens.
20163

About Vivek V. Datla

Vivek V. Datla is a scholar working on Artificial Intelligence, Molecular Biology, Social Psychology, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 26 papers that have together received 422 indexed citations. Recurring topics across this work include Topic Modeling (16 papers), Biomedical Text Mining and Ontologies (10 papers), Natural Language Processing Techniques (9 papers), Machine Learning in Healthcare (6 papers), Multimodal Machine Learning Applications (3 papers), Advanced Text Analysis Techniques (3 papers), Intelligent Tutoring Systems and Adaptive Learning (2 papers) and Misinformation and Its Impacts (2 papers). The work is most often cited by research in Artificial Intelligence (270 citations), Toxicology (25 citations), Health Information Management (21 citations), Computer Networks and Communications (76 citations) and Information Systems (63 citations). Vivek V. Datla has collaborated with scholars based in United States, Finland and India. Frequent co-authors include Joey Liu, Ashequl Qadir, Oladimeji Farri, Sadid A. Hasan, Kathy Lee, Aaditya Prakash, Qishi Wu, Siyuan Zhao, Charles D. Ellis and Sajjan G. Shiva. Their work appears in journals such as Cognitive Science, Lecture notes in computer science, International Conference on Computational Linguistics, Educational Data Mining and National Conference on Artificial Intelligence.

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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