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  • Rae A, Kim J, Le DX, Thoma GR. Main Content Detection in HTML Journal Articles. DocEng ’18: ACM Symposium on Document Engineering 2018, August 28–31, 2018, Halifax, NS, Canada. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3209280.3229115
  • Kim I, Thoma GR. Automated Identification of Potential Conflict-of-Interest in Biomedical Articles Using Hybrid Deep Neural Network. Proc. 14th Int’l Conf. Machine Learning and Data Mining (MLDM 2018), LNAI 10934, pp. 99-112, Newark, NJ, July 2018.
  • Kim I, Thoma GR. Automated Identification of Potential Conflict-of-Interest in Biomedical Articles Using Hybrid Deep Neural Network. Proc. 14th Int’l Conf. Machine Learning and Data Mining (MLDM 2018), LNAI 10934, pp. 99-112, Newark, NJ, July 2018.
  • Zou J, Antani SK, Thoma GR. Localizing and Recognizing Labels for Multi-Panel Figures in Biomedical Journals. Proceedings of International Conference on Document Analysis and Recognition, November 13, 2017
  • Mrabet Y, Kilicoglu H, Demner-Fushman D. TextFlow: A Text Similarity Measure based on Continuous Sequences. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017, Vancouver, Canada, July 30 - August 4, Volume
  • Kim I, Thoma GR. Machine Learning with Selective Word Statistics for Automated Classification of Citation Subjectivity in Online Biomedical Articles. Proc. Int’l Conf. Artificial Intelligence (ICAI’17), pp. 201-207, Las Vegas, July 2017.
  • Kim J, Hong S, Thoma GR. Labeling Author Affiliations in Biomedical Articles Using Markov Model Classifiers. The 13th International Conference on Data Mining (DMIN2017), pp. 105-110, Las Vegas, USA, July 2017.
  • Chachra S, Ben Abacha A, Shooshan SE, Rodriguez L, Demner-Fushman D. A Hybrid Approach to Generation of Missing Abstracts in Biomedical Literature. Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers: 1093-1100.
  • De Herrera A, Schaer R, Antani SK, Müller H. Using Crowdsourcing for Multi-label Biomedical Compound Figure Annotation. In: Carneiro G. et al. (eds) Deep Learning and Data Labeling for Medical Applications. LABELS 2016, DLMIA 2016. Lecture Notes in Computer Science, vol 10008. Springer, Cham
  • Narum R, Zou J, Antani SK. Semi-Automated Ground-Truth Data Collection and Annotation for Journal Figure Analysis [Poster]. 2016 NIH Research Festival
  • Rodriguez L, Morrison SM, Greenberg K, Demner-Fushman D. Towards Automatic Discovery of Genes Related to Human Placenta [Poster]. Poster Fall AMIA 2016.
  • Xue Z, Rahman M, Antani SK, Long LR, Demner-Fushman D, Thoma GR. Modality Classification for Searching Figures in Biomedical Literature. Proceedings of the IEEE 29th International Symposium on Computer-Based Medical Systems, pp. 152-157, 2016. doi:10.1109/CBMS.2016.29.
  • Kim J, Thoma GR. Named Entity Recognition in Affiliations of Biomedical Articles Using Statistics and HMM Classifiers. The 2016 International Conference on Data Mining (DMIN2016), Las Vegas, USA, pp. 236-241, July, 2016.
  • Kim J, Lobuglio PS, Thoma GR. Visualization of Statistics from MEDLINE. 2016 IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS 2016), Dublin and Belfast, Ireland, pp. 290-291, June, 2016.
  • Kim I, Thoma GR. Automated Classification of Author’s Sentiments in Citation Using Machine Learning Techniques: A Preliminary Study. Proc. the 2015 IEEE Conf. Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2015), Niagara Falls, Canada, Aug. 12-15, 2015.
  • Kim J, Le DX, Thoma GR. Identification of Investigator Name Zones Using SVM Classifiers and Heuristic Rules. 12th international Conference on Document Analysis and Recognition (ICDAR). Washington D.C., August 2013.
  • Misra D, Thoma GR. Use of descriptive metadata as a knowledgebase for analyzing data in large textual collections. Proc. IS&T Archiving 2013. Washington D.C. Proc. IS&T Archiving 2013. Washington D.C. pg 193-199.
  • Kim I, Le DX, Thoma GR. Identifying “comment-on” citation data in online biomedical articles using SVM-based text summarization technique. Proc. Int’l Conf. Artificial Intelligence (ICAI’12), vol. 1, pp. 431-437, Las Vegas, July 2012.
  • Misra D, Hall RH, Payne SM, Thoma GR. Digital preservation and knowledge discovery based on documents from an international health science program. Proc. 12th ACM/IEEE-CS JCDL, pg 23-26 (2012). doi: 10.1145/2232817.2232823.
  • Kim J, Le DX, Thoma GR. Combining SVM Classifiers to Identify Investigator Name Zones in Biomedical Articles. IS&T/SPIE’s 22nd Annual Symposium on Electronic Imaging. San Francisco, CA, January 2012; 8297.
  • Kim I, Le DX, Thoma GR. Automated identification of biomedical article type using support vector machines. Proc. 18th SPIE Document Recognition and Retrieval, 7874:787403 (1-9), San Francisco, January 2011.
  • Zhang X, Zou J, Le DX, Thoma GR. Investigator Name Recognition From Medical Journal Articles: A Comparative Study of SVM and Structural SVM International Workshop on Document Analysis Systems. June 2010:121-8
  • Chen S, Misra D, Thoma GR. Efficient Automatic OCR Word Validation Using Word Partial Format Derivation and Language Model Document Recognition and Retrieval XVII. Proceedings of the SPIE. San Jose, CA. January 2010;7534:75340O-75340O-8
  • Kim J, Le DX, Thoma GR. Naive Bayes and SVM Classifiers For Classifying Databank Accession Number Sentences From Online Biomedical Articles IS&T/SPIE's 22nd Annual Symposium on Electronic Imaging. San Jose, CA. January 2010;7534:75340U-1 - 8
  • Zhang X, Zou J, Le DX, Thoma GR. A Stacked Sequential Learning Method For Investigator Name Recognition From Web-based Medical Articles 17th Document Recognition and Retrieval Conference (SPIE-DR&R). San Jose, CA. January 2010;7534:753404-7

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