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Tung Tran

Publications

3 granted U.S. patents and 1 pending application, and 16 papers: 9 in journals, 6 in proceedings and 1 preprint. Citation counts are on Google Scholar; the full record is on dblp.

  1. Systems and methods for automatic generation of social media networks and interactions

    Granted June 2026 · Second patent from the same 2021 filing as US 12,476,877 B2 · Pending in Europe, Australia and Canada · with D. Shin

    US 12,664,214 B2

  2. Systems and methods for automatic generation of social media networks and interactions

    Granted November 2025 · Pending in Europe, Australia and Canada · with D. Shin

    US 12,476,877 B2

  3. Systems and methods for artificial facial image generation conditioned on demographic information

    Granted April 2025 · Pending in Europe, Australia and Canada · with D. Shin, J. D. Hoye, M. R. Ehlers

    US 12,287,847 B2

  4. Scenario-based cyber network topology generation system and method

    Filed January 2026, pending · with J. D. Hoye, N. Melgar

    WO 2026/156353 A1US 2026/0222449 A1

Papers

2021

  1. Identifying Current Juul Users among Emerging Adults through Twitter Feeds

    T. Tran, M. Ickes, J. W. Hester, and R. Kavuluru · International Journal of Medical Informatics, 2021

    pdfdoi

    @article{tran2020identifying,  title = {{Identifying Current Juul Users among Emerging Adults through Twitter Feeds}},  author = {T. Tran and M. Ickes and J. W. Hester and R. Kavuluru},  journal = {International Journal of Medical Informatics},  year = {2021},  volume = {146},  pages = {104350},  doi = {10.1016/j.ijmedinf.2020.104350}}
  2. Attention-Gated Graph Convolutions for Extracting Drug Interaction Information from Drug Labels

    T. Tran, R. Kavuluru, and H. Kilicoglu · ACM Transactions on Computing for Healthcare, 2021

    pdfdoi

    @article{tran2020attention,  title = {{Attention-Gated Graph Convolutions for Extracting Drug Interaction Information from Drug Labels}},  author = {T. Tran and R. Kavuluru and H. Kilicoglu},  journal = {ACM Transactions on Computing for Healthcare},  year = {2021},  doi = {10.1145/3423209}}

2020

  1. Social Media Surveillance for Perceived Therapeutic Effects of Cannabidiol (CBD) Products

    T. Tran and R. Kavuluru · International Journal of Drug Policy, 2020

    pdfdoi

    @article{tran2020social,  title = {{Social Media Surveillance for Perceived Therapeutic Effects of Cannabidiol (CBD) Products}},  author = {T. Tran and R. Kavuluru},  journal = {International Journal of Drug Policy},  year = {2020},  doi = {10.1016/j.drugpo.2020.102688}}

2019

  1. Distant Supervision for Treatment Relation Extraction by Leveraging MeSH Subheadings

    T. Tran and R. Kavuluru · Artificial Intelligence in Medicine, 2019

    pdfdoi

    @article{tran2019distant,  title = {{Distant Supervision for Treatment Relation Extraction by Leveraging MeSH Subheadings}},  author = {T. Tran and R. Kavuluru},  journal = {Artificial Intelligence in Medicine},  year = {2019},  doi = {10.1016/j.artmed.2019.06.002}}
  2. Confirm or Refute?: A Comparative Study on Citation Sentiment Classification in Clinical Research Publications

    H. Kilicoglu, Z. Peng, S. Tafreshi, T. Tran, G. Rosemblat, and J. Schneider · Journal of Biomedical Informatics, 2019

    doi

    @article{kilicoglu2019confirm,  title = {{Confirm or Refute?: A Comparative Study on Citation Sentiment Classification in Clinical Research Publications}},  author = {H. Kilicoglu and Z. Peng and S. Tafreshi and T. Tran and G. Rosemblat and J. Schneider},  journal = {Journal of Biomedical Informatics},  year = {2019},  doi = {10.1016/j.jbi.2019.103123}}
  3. Overview of the BioCreative VI Precision Medicine Track: Mining Protein Interactions and Mutations for Precision Medicine

    R. Doğan, S. Kim, A. Chatr-aryamontri, C. Wei, D. Comeau, and 22 others, including T. Tran · Database: The Journal of Biological Databases and Curation, 2019

    doi

    @article{dogan2019overview,  title = {{Overview of the BioCreative VI Precision Medicine Track: Mining Protein Interactions and Mutations for Precision Medicine}},  author = {R. Doğan and S. Kim and A. Chatr-aryamontri and C. Wei and D. Comeau and others},  journal = {Database: The Journal of Biological Databases and Curation},  year = {2019},  doi = {10.1093/database/bay147}}
  4. Neural Metric Learning for Fast End-to-End Relation Extraction

    T. Tran and R. Kavuluru · arXiv preprint arXiv:1905.07458, 2019

    pdf

    @misc{tran2020neural,  title = {{Neural Metric Learning for Fast End-to-End Relation Extraction}},  author = {T. Tran and R. Kavuluru},  howpublished = {arXiv preprint arXiv:1905.07458},  year = {2019},  url = {https://arxiv.org/pdf/1905.07458.pdf}}

2018

  1. A Multi-Task Learning Framework for Extracting Drugs and Their Interactions from Drug Labels

    T. Tran, R. Kavuluru, and H. Kilicoglu · Proceedings of the Eleventh Text Analysis Conference (TAC 2018), 2018

    report

    @inproceedings{tran2018multi,  title = {{A Multi-Task Learning Framework for Extracting Drugs and Their Interactions from Drug Labels}},  author = {T. Tran and R. Kavuluru and H. Kilicoglu},  booktitle = {Proceedings of the Eleventh Text Analysis Conference (TAC 2018)},  year = {2018},  url = {https://tac.nist.gov/publications/2018/participant.papers/TAC2018.ttran.proceedings.pdf}}
  2. Data and Systems for Medication-Related Text Classification and Concept Normalization from Twitter: Insights from the Social Media Mining for Health (SMM4H) 2017 Shared Task

    A. Sarker, M. Belousov, J. Friedrichs, K. Hakala, S. Kiritchenko, F. Mehryary, S. Han, T. Tran, and 8 others · Journal of the American Medical Informatics Association, 2018

    doi

    @article{sarker2018data,  title = {{Data and Systems for Medication-Related Text Classification and Concept Normalization from Twitter: Insights from the Social Media Mining for Health (SMM4H) 2017 Shared Task}},  author = {A. Sarker and M. Belousov and J. Friedrichs and K. Hakala and S. Kiritchenko and F. Mehryary and S. Han and T. Tran and others},  journal = {Journal of the American Medical Informatics Association},  year = {2018},  volume = {25},  number = {10},  pages = {1274--1283},  doi = {10.1093/jamia/ocy114}}
  3. An End-to-End Deep Learning Architecture for Extracting Protein–Protein Interactions Affected by Genetic Mutations

    T. Tran and R. Kavuluru · Database: The Journal of Biological Databases and Curation, 2018

    pdfdoi

    @article{tran2018end,  title = {{An End-to-End Deep Learning Architecture for Extracting Protein–Protein Interactions Affected by Genetic Mutations}},  author = {T. Tran and R. Kavuluru},  journal = {Database: The Journal of Biological Databases and Curation},  year = {2018},  doi = {10.1093/database/bay092}}
  4. Predicting Psychological Health from Childhood Essays with Convolutional Neural Networks for the CLPsych 2018 Shared Task (Team UKNLP)

    A. Rios, T. Tran, and R. Kavuluru · Proceedings of the Fifth Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2018), 2018

    publisher

    @inproceedings{rios2018predicting,  title = {{Predicting Psychological Health from Childhood Essays with Convolutional Neural Networks for the CLPsych 2018 Shared Task (Team UKNLP)}},  author = {A. Rios and T. Tran and R. Kavuluru},  booktitle = {Proceedings of the Fifth Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2018)},  year = {2018},  url = {https://aclanthology.org/W18-0611/}}

2017

  1. Supervised Approaches to Assign Cooperative Patent Classification (CPC) Codes to Patents

    T. Tran and R. Kavuluru · Proceedings of the Fifth International Conference on Mining Intelligence and Knowledge Exploration (MIKE 2017), 2017

    pdfdoi

    @inproceedings{tran2017supervised,  title = {{Supervised Approaches to Assign Cooperative Patent Classification (CPC) Codes to Patents}},  author = {T. Tran and R. Kavuluru},  booktitle = {Proceedings of the Fifth International Conference on Mining Intelligence and Knowledge Exploration (MIKE 2017)},  year = {2017},  pages = {22--34},  publisher = {Springer},  doi = {10.1007/978-3-319-71928-3_3}}
  2. Exploring a Deep Learning Pipeline for the BioCreative VI Precision Medicine Task

    T. Tran and R. Kavuluru · Proceedings of the BioCreative VI Workshop (BC VI), 2017

    reportproceedings

    @inproceedings{tran2017exploring,  title = {{Exploring a Deep Learning Pipeline for the BioCreative VI Precision Medicine Task}},  author = {T. Tran and R. Kavuluru},  booktitle = {Proceedings of the BioCreative VI Workshop (BC VI)},  year = {2017},  url = {http://protocols.netlab.uky.edu/~rvkavu2/research/tran-biocreative.pdf}}
  3. Team UKNLP: Detecting ADRs, Classifying Medication Intake Messages, and Normalizing ADR Mentions on Twitter

    S. Han, T. Tran, A. Rios, and R. Kavuluru · Proceedings of the 2nd Social Media Mining for Health Applications Workshop and Shared Task at AMIA (SMM4H 2017), 2017

    report

    @inproceedings{han2017team,  title = {{Team UKNLP: Detecting ADRs, Classifying Medication Intake Messages, and Normalizing ADR Mentions on Twitter}},  author = {S. Han and T. Tran and A. Rios and R. Kavuluru},  booktitle = {Proceedings of the 2nd Social Media Mining for Health Applications Workshop and Shared Task at AMIA (SMM4H 2017)},  year = {2017},  url = {https://ceur-ws.org/Vol-1996/paper9.pdf}}
  4. Extracting Drug-Drug Interactions with Word and Character-Level Recurrent Neural Networks

    R. Kavuluru, A. Rios, and T. Tran · Proceedings of the Fifth IEEE International Conference on Healthcare Informatics (ICHI 2017), Workshop on Healthcare Knowledge Discovery and Management, 2017

    pdfdoislides

    @inproceedings{kavuluru2017extracting,  title = {{Extracting Drug-Drug Interactions with Word and Character-Level Recurrent Neural Networks}},  author = {R. Kavuluru and A. Rios and T. Tran},  booktitle = {Proceedings of the Fifth IEEE International Conference on Healthcare Informatics (ICHI 2017), Workshop on Healthcare Knowledge Discovery and Management},  year = {2017},  doi = {10.1109/ICHI.2017.15}}
  5. Predicting Mental Conditions Based on “History of Present Illness” in Psychiatric Notes with Deep Neural Networks

    T. Tran and R. Kavuluru · Journal of Biomedical Informatics, 2017

    pdfdoislides

    @article{tran2017predicting,  title = {{Predicting Mental Conditions Based on "History of Present Illness" in Psychiatric Notes with Deep Neural Networks}},  author = {T. Tran and R. Kavuluru},  journal = {Journal of Biomedical Informatics},  year = {2017},  doi = {10.1016/j.jbi.2017.06.010}}