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  • Bodenreider O, Azuaje F. Incorporating Ontology-Driven Similarity Knowledge Into Functional Genomics: An Exploratory Study Proceedings of the 2004 IEEE Fourth Symposium on Bioinformatics and Bioengineering (BIBE-2004) 2004:317-324.
  • Bodenreider O, Smith B, Burugn A. The Ontology-Epistemology Divide: A Case Study in Medical Terminology Proceedings of the Third International Conference on Formal Ontology in Information Systems (FOIS2004): IOS Press; 2004. p. 185-195.
  • Bodenreider O, Mitchell JA. Graphical Visualization and Navigation of Genetic Disease Information AMIA Annu Symp Proc. 2003:792.
  • Bodenreider O. Strength in Numbers: Exploring Redundancy in Hierarchical Relations Across Biomedical Terminologies AMIA Annu Symp Proc. 2003:101-5.
  • Bodenreider O. A Semantic Navigation Tool for the UMLS AMIA Annu Symp Proc. 2000;: 971.
  • Bodenreider O. Comment les Usagers Accedent a l'Information Medicale Aux USA: l'Exemple de MEDLINEplus [How Consumers Access Health Information in the USA: The MEDLINEplus Example] Innovation et Technologie en Biologie et Medecine. 2000;21(5):286-90.
  • Bodenreider O, Mitchell JA, McCray AT. Evaluation of the UMLS as a Terminology and Knowledge Resource for Biomedical Informatics Proc AMIA Symp. 2002:61-65.
  • Bodenreider O, Zweigenbaum P. Strategies d'Identification des Noms Propres a Partir de Nomenclatures Medicales Paralleles Traitement Automatique des Langues. 2000;41(3):727-757.
  • Bodenreider O. Circular hierarchical relationships in the UMLS: etiology, diagnosis, treatment, complications and prevention. Proc AMIA Symp. 2001:57-61.
  • Bodenreider O, Zweigenbaum P. Identifying Proper Names in Parallel Medical Terminologies Stud Health Technol Inform. 2000;77:443-7
  • Bodenreider O. Using UMLS semantics for classification purposes. Proc AMIA Symp. 2000:86-90.
  • Botti G, Bodenreider O, Burgun A, Le Beux P, Fieschi M. De la Classification à la Connaissance des Maladies: Une Réflexion à Partir de la Classification Internationale des Maladies [From Classification to Knowledge About Diseases: Thoughts about the International Classification of Diseases] Innovation et Technologie en Biologie et Médecine. 2000;21(5):291-97.
  • Boyce RD, Voss EA, Huser V, Evans L, Reich C, Duke JD, Tatonetti NP, Lorberbaum T, Dumontier M, Hauben M, Wallberg M. LAERTES: An open scalable architecture for linking pharmacovigilance evidence sources with clinical data. Proc International Conference on Biomedical Ontology and BioCreative (ICBO BioCreative 2016). http://icbo2016.cgrb.oregonstate.edu/node/354.
  • Boyce RD, Ryan PB, Noren GN, Schuemie MJ, Reich C, Duke J, Tatonetti NP, Trifiro G, Harpaz R, Overhage JM, Hartzema AG, Kayter M, Voss EA, Lambert CG, Huser V, Dumontier M. Bridging islands of information to establish an integrated knowledge base of drugs and health outcomes of interest. Drug Saf. 2014 Aug;37(8):557-67. doi: 10.1007/s40264-014-0189-0.
  • Burgun A, Mougin F, Bodenreider O. Two approaches to integrating phenotype and clinical information. AMIA Annu Symp Proc. 2009 Nov 14;2009:75-9.
  • Burgun A, Bodenreider O. Accessing and Integrating Data and Knowledge for Biomedical Research Yearb Med Inform. 2008:91-101
  • Bush R, Heierman E, Knafel A, Lardin L, McDonald CJ. LIVD – Digital Format for Publication of LOINC to Vendor IVD Test Results. . IVD Industry Connectivity Consortium. http://ivdconnectivity.org/livd/. Published June 1, 2017. Accessed August 9, 2017.
  • Cahan A, Cimino JJ. Improving precision medicine using individual patient data from trials. CMAJ. 2017 Feb 6;189(5):E204-E207. doi: 10.1503/cmaj.160267. Epub 2016 Aug 29.
  • 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.
  • Cameron D, Bodenreider O, Yalamanchili H, Danh T, Vallabhaneni S, Thirunarayan K, Sheth AP, Rindflesch TC. A graph-based recovery and decomposition of Swanson's hypothesis using semantic predications. J Biomed Inform. 2013 Apr;46(2):238-51. doi: 10.1016/j.jbi.2012.09.004. Epub 2012 Sep 28.
  • Cameron D, Kavuluru R, Bodenreider O, Mendes PN, Sheth AP, Thirunarayan K. Semantic predications for complex information needs in biomedical literature BIBM 2011:512-519.
  • Campbell JR, Xu J, Fung K. Can SNOMED CT fulfill the vision of a compositional terminology? Analyzing the use case for problem list. AMIA Annu Symp Proc. 2011;2011:181-8. Epub 2011 Oct 22.
  • Candemir S, Jaeger S, Palaniappan K, Musco J, Singh RK, Xue Z, Karargyris A, Antani SK, Thoma GR, McDonald CJ. Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration. IEEE Trans Med Imaging. 2014 Feb;33(2):577-90. doi: 10.1109/TMI.2013.2290491. Epub 2013 Nov 13.
  • Cardillo E, Hernandez, Jr G, Bodenreider O. Integrating consumer-oriented vocabularies with selected professional ones from the UMLS using Semantic Web Technologies. Proceedings of the eHealth 2010 conference, 2010: p. (paper 10579 - electronic proceedings).

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