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  • Tolentino HD, Matters MD, Walop W, Law B, Tong W, Liu F, Fontelo P, Kohl K, Payne DC. A UMLS-based Spell Checker for Natural Language Processing in Vaccine Safety. BMC Med Inform Decis Mak. 2007 Feb 12;7:3. DOI: 10.1186/1472-6947-7-3.
  • Keselman A, Rosemblat G, Kilicoglu H, Fiszman M, Jin H, Shin D, Rindflesch TC. Adapting Semantic Natural Language Processing Technology to Address Information Overload in Influenza Epidemic Management Journal of the American Society for Information Science and Technology (JASIST), 61(12):2531-2543, 2010
  • Lynch P, Luan X, Prettyman M, Mericle L, Borkmann E, Schlaifer J. An evaluation of new and old similarity ranking algorithms. Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC’04). 2004;2:148.
  • Resnick MP, Ripple AM, Auston I, Rindflesch TC. An Ontology for Public Health to Support Enhanced Information Retrieval AMIA Annu Symp Proc. 2010
  • Sahoo SS, Bodenreider O, Rutter JL, Skinner KJ, Sheth AP. An Ontology-driven Semantic Mash-up of Gene and Biological pathway information: Application to the domain of nicotine dependence J Biomed Inform. 2008 Oct;41(5):752-65. Epub 2008 Feb 29
  • Aronson AR, Lang FM. An overview of MetaMap: historical perspective and recent advances. J Am Med Inform Assoc. 2010 May-Jun;17(3):229-36. doi: 10.1136/jamia.2009.002733.
  • Roberts K, Demner-Fushman D. Annotating Logical Forms for EHR Questions. Proceedings of the Language Resources and Evaluation Conference, LREC,23-28 May 2016, Portorož.
  • Demner-Fushman D, Lin J. Answer Extraction, Semantic Clustering, and Extractive Summarization for Clinical Question Answering Proc COLING/ACL 2006. July 2006, Sydney, Australia
  • Demner-Fushman D, Lin J. Answering Clinical Questions with Knowledge-based and Statistical Techniques Computational Linguistics. 2007 Jan;33(1):63-103
  • Hanauer DA, Saeed M, Zheng K, Mei Q, Shedden K, Aronson AR, Ramakrishnan N. Applying MetaMap to Medline for identifying novel associations in a large clinical dataset: a feasibility analysis. J Am Med Inform Assoc. 2014 Sep-Oct;21(5):925-37. doi: 10.1136/amiajnl-2014-002767. Epub 2014 Jun 13.
  • Misra D, Mao S, Rees J, Thoma GR. Archiving a Historic Medico-legal Collection: Automation and Workflow Customization Proc IS&T Archiving 2007. Arlington, Virginia, May 2007; 157-61
  • Rindflesch TC, Bean CA, Sneiderman CA. Argument Identification for Arterial Branching Predications Asserted in Cardiac Catheterization Reports Proc AMIA Symp. 2000:704-8.
  • Masseroli M, Kilicoglu H, Lang F-M, Rindflesch TC. Argument-predicate Distance as a Filter for Enhancing Precision in Extracting Predications on the Genetic Etiology of Disease. BMC Bioinformatics. 2006 Jun 8;7:291.
  • Ruch P, Tbahriti I, Bobeill J, Aronson AR. Argumentative Feedback: A Linguistically-motivated Term Expansion for Information Retrieval Proc COLING/ACL 2006, 675-82
  • Kilicoglu H, Fiszman M, Rosemblat G, Marimpietri S, Rindflesch TC. Arguments of Nominals in Semantic Interpretation of Biomedical Text BioNLM Workshop Proc, Assoc. for Computational Linguistics 2010
  • Keselman A, Tse T, Crowell J, Browne AC, Ngo L, Zeng Q. Assessing Consumer Health Vocabulary Familiarity: An Exploratory Study J Med Internet Res. 2007 Mar 14;9(1):e5
  • Kilicoglu H, Rosemblat G, Rindflesch TC. Assigning factuality values to semantic relations extracted from biomedical research literature. PLoS One. 2017 Jul 5;12(7):e0179926. doi: 10.1371/journal.pone.0179926. eCollection 2017.
  • 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.
  • Zhang, K, Demner-Fushman D. Automated classification of eligibility criteria in clinical trials to facilitate patient-trial matching for specific patient populations. J Am Med Inform Assoc. 2017 Jul 1;24(4):781-787. doi: 10.1093/jamia/ocw176.
  • Kim I, Le DX, Thoma GR. Automated Cleanup Processing for Extracting Bibliographic Data from Biomedical Online Journals In: Callaos N, Lesso W, editors. SCI 2005. Proc. 9th World Multiconference on Systemics, Cybernetics and Informatics; 2005 Jul 10-13; Vol. 4; Orlando (FL): International Institute of Informatics and Systemics; c2005. 401-5
  • 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.
  • 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.
  • Kim J, Le DX, Thoma GR. Automated Labeling Of Biomedical Online Journal Articles In: Callaos N, Lesso W, editors. SCI 2005. Proc 9th World Multiconference on Systemics, Cybernetics and Informatics; 2005 Jul 10-13; Vol. 4; Orlando (FL): International Institute of Informatics and Systemics; c2005. 406-11
  • Thoma GR, Mao S, Misra D. Automated Metadata Extraction to Preserve the Digital Contents of Biomedical Collections Proc VIIP 2005. September 2005. Benidorm, Spain; 214-19

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