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  • Abhyankar S, Demner-Fushman D. A simple method to extract key maternal data from neonatal clinical notes. AMIA Annu Symp Proc. 2013 Nov 16;2013:2-9. eCollection 2013.
  • Ben Abacha A. NLM_NIH at TREC 2016 Clinical Decision Support Track. Proceedings of TREC 2016, the 25th Text Retrieval Conference, Gaithersburg, MD, USA, November 2016.
  • Bodenreider O, Demner-Fushman D. Investigating drug classes in biomedical terminologies from the perspective of clinical decision support. AMIA Annu Symp Proc. 2010 Nov 13;2010:56-60.
  • Callaghan F, Jackson MT, Demner-Fushman D, Abhyankar S, McDonald C. Analysis of data that has been extracted from free-text using natural language processing: a likelihood model for misclassification with an application to medical informatics. International Conference on Advances in Interdisciplinary Statistics and Combinatorics (AISC2012), Greensboro, NC, October 2012
  • Callaghan F, Jackson MT, Demner-Fushman D, Abhyankar S, McDonald CJ. NLP-derived information improves the estimates of risk of disease compared to estimates based on manually extracted data alone. 5th International Symposium on Semantic Mining in Biomedicine (SMBM 2012), 2012 Sept 3-4, Zurich, Switzerland.
  • 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.
  • 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
  • Chen S, Mao S, Thoma GR. Simultaneous Layout Style and Logical Entity Recognition in a Heterogeneous Collection of Documents Proc ICDAR2007. Curitiba, Brazil; September 2007, pp. 118-22
  • 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
  • Demner-Fushman D, Karpinski J, Thoma GR. Automatically building a repository to support evidence-based practice. Proceedings of the 2nd Workshop on Building and evaluating resources for biomedical text mining (BioTxtM 2010), 7th Language Resources and Evaluation Conference (LREC 2010). Valetta, Malta. May 2010.
  • Demner-Fushman D, Seckman C, Fisher C, Hauser SE, Clayton J, Thoma GR. A prototype system to support evidence-based practice AMIA Annu Symp Proc. 2008 Nov 6:151-5.
  • Demner-Fushman D, Humphrey SM, Ide NC, Loane RF, Ruch P, Ruiz ME, Smith LH, Tanabe LK, Wilbur WJ, Aronson AR. Finding Relevant Passages in Scientific Articles: Fusion of Automatic Approaches vs. an Interactive Team Effort. Proc TREC 2006, 569-76.
  • Demner-Fushman D, Hauser SE, Thoma GR. The role of title, metadata and abstract in identifying clinically relevant journal articles. AMIA Annu Symp Proc. 2005:191-5.
  • Edinger T, Demner-Fushman D, Cohen AM, Bedrick S, Hersh W. Evaluation of Clinical Text Segmentation to Facilitate Cohort Retrieval. AMIA Annu Symp Proc. 2018 Apr 16;2017:660-669. eCollection 2017.
  • Hauser SE, Le DX, Thoma GR. Automated Zone Correction in Bitmapped Document Images SPIE: Document Recognition and Retrieval VII. 2000 Jan;3976: 248-58.
  • Huang X, Lin J, Demner-Fushman D. Evaluation of PICO as a knowledge representation for clinical questions AMIA Annu Symp Proc. 2006:359-63.
  • 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 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 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 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.
  • 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, 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 IC, Le DX, Thoma GR. Hybrid approach combining contextual and statistical information for identifying and statistical information for identifying MEDLINE citation terms. Proc. SPIE-IS/T Electronic Imaging. San Jose, CA. January 2008;6815:68150P(1-9)
  • Kim IC, Le DX, Thoma GR. Identification of "comment-on sentences" in online biomedical documents using support vector machines. Proc. SPIE conference on Document Recognition and Retrieval, 6500:65000O (1-8), San Jose, January 2007.

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