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  • Patel CO, Cimino JJ. Using Semantic and Structural Properties of the UMLS to Discover Potential Terminological Relationships AMIA Annu Symp Proc. 2008 Nov 6:555.
  • Bodenreider O. Using SNOMED CT in combination with MedDRA for reporting signal detection and adverse drug reactions reporting. AMIA Annu Symp Proc. 2009 Nov 14;2009:45-9.
  • Wei D, Bodenreider O. Using the abstraction network in complement to description logics for quality assurance in biomedical terminologies - a case study in SNOMED CT. Stud Health Technol Inform. 2010;160(Pt 2):1070-4.
  • Peters L, Bodenreider O. Using the RxNorm Web Services API for Quality Assurance Purposes AMIA Annu Symp Proc. 2008 Nov 6:591-5.
  • Bodenreider O. Using UMLS semantics for classification purposes. Proc AMIA Symp. 2000:86-90.
  • Mougin F, Burgun A, Bodenreider O. Using WordNet to Improve the Mapping of Data Elements to UMLS for Data Sources Integration AMIA Annu Symp Proc. 2006:574-8
  • Fung KW, Bodenreider O. Utilizing the UMLS for Semantic Mapping between Terminologies. AMIA Annu Symp Proc. 2005:266-70.
  • Fontelo P, DiNino E, Johansen K, Khan A, Ackerman MJ. Virtual Microscopy: Potential Applications in Medical Education and Telemedicine in Countries with Developing Economies. Proceedings of the 38th Hawaii International Conference on System Sciences; 2005 Jan 3-6; Big Island, Hawaii: 7 pages. IEEE Computer Society.
  • Ratiu P, Hillen B, Glaser J, Jenkins DB. Visible Human 2.0 - The Next Generation. In: Westwood JD, Hoffman HM, Mogel GT, Phillips R, Robb RA, Stredney D, editors. Stud Health Technol Inform [Studies in Health Technology and Informatics] -- Proceedings of the 11th annual Medicine Meets Virtual Reality conference; 2003 Jan;94:275-81. Amsterdam: IOS Press.
  • Ackerman MJ. Visible Human Project. McGraw-Hill 2004 Yearbook of Science & Technology. New York: McGraw-Hill. 2004. p. 369-72.
  • Ackerman MJ. Visible Human Project: From Data to Knowledge. In: Haux R, Kulikowski C, editors. Yearbook of Medical Informatics 2002: Medical Imaging Informatics. International Medical Informatics Association (IMIA). p. 115-7.
  • 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.
  • Rajaraman S, Antani SK, Xue Z, Candemir S, Jaeger S, Thoma GR. Visualizing abnormalities in chest radiographs through salient network activations in Deep Learning. Proc. IEEE Life Sciences Conference (LSC), Sydney, Australia, 2017. pp. 71-74, DOI:10.1109/LSC.2017.8268146.
  • Rajaraman S, Candemir S, Thoma G, Antani SK. Visualizing and explaining deep learning predictions for pneumonia detection in pediatric chest radiographs. Proc. SPIE 10950, Medical Imaging 2019: Computer-Aided Diagnosis, 109500S (13 March 2019); doi: 10.1117/12.2512752.
  • Rajaraman S, Antani SK, Jaeger S. Visualizing Deep Learning Activations for Improved Malaria Cell Classification. Proceedings of The First Workshop in Medical Informatics and Healthcare (MIH 2017), Proceedings of Machine Learning Research (PMLR), v. 69, p. 40-47.
  • Xue Z, Antani S, Long LR, Thoma GR. Web-accessible Cervigram Automatic Segmentation Tool SPIE Medical Imaging Conference. March 2010;7628
  • Walker FL, Thoma GR. Web-Based Document Image Processing Proc. SPIE: Internet Imaging. 2000 Jan;:268-77.
  • Zhu Y, Huang X, Lopresti D, Long R et al. Web-based Multi-observer Segmentation Evaluation Tool Proc. 21st IEEE CBMS. Jyvaskyla, Finland. June 2008:167-9
  • Fung KW, Hole WT, Srinivasan S. Who is using the UMLS and how - insights from the UMLS user annual reports. AMIA Annu Symp Proc. 2006:274-8.
  • Kayaalp M. Why Do We Need Probabilistic Approaches to Ontologies and the Associated Data? AMIA Annu Symp Proc. 2005:1005
  • Xue Z, Antani SK, Long LR, Demner-Fushman D, Thoma GR. Window classification of brain CT images in biomedical articles. AMIA Annu Symp Proc. 2012;2012:1023-9. Epub 2012 Nov 3.

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