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  • Zou J, Antani SK, Thoma G. Unified Deep Neural Network for Segmentation and Labeling of Multi-Panel Biomedical Figures Journal of the Association for Information Science and Technology (JASIST), 2019
  • Zou J. Unified Deep Neural Network for Segmentation and Labeling of Multi-Panel Biomedical Figures Journal of the Association for Information Science and Technology (JASIST), 2019
  • Alzamzmi GA, Rajaraman S, Antani SK. Unified Representation Learning for Efficient Medical Image Analysis 2020, [Online]
  • Mrabet Y, Kilicoglu H, Demner-Fushman D. Unsupervised Ranking of Knowledge Bases for Named Entity Recognition. ECAI 2016, The Hague, The Netherlands, 1248-1255.
  • Tse T, Williams RJ, Zarin DA. Update on Registration of Clinical Trials in ClinicalTrials.gov. Chest. 2009 Jul;136(1):304-5. doi: 10.1378/chest.09-1219.
  • McCray AT, Dorfman E, Ripple A, Ide NC, Jha M, Katz DG, Loane RF, Tse T. Usability Issues in Developing a Web-Based Consumer Health Site Proc AMIA Symp. 2000:556-60.
  • Long LR, Thoma GR. Use of Shape Models to Search Digitized Spine X-Rays IEEE Computer-Based Medical Systems. 2000 June;: 255-60.
  • Xue Z, Antani SK, Long LR, Thoma GR. Using deep learning for detecting gender in adult chest radiographs. Proc SPIE 10579, Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications, 105790D (6 March 2018) pp. doi: 10.1117/12.2293027.
  • Xue Z, Antani SK, Long LR, Thoma GR. Using deep learning for detecting gender in adult chest radiographs. SPIE Medical Imaging 2018
  • Collins H, Calvo SC, Greenberg K, Forman NL, Morrison SM. Using Genetics Home Reference to Reinforce Patient Education [Poster]. American College of Medical Genetics Annual Meeting, Phoenix, AZ, March 21-25, 2017.
  • Beaudoin DE, Longo N, Logan RA, Jones JP, Mitchell JA. Using information prescriptions to refer patients with metabolic conditions to the Genetics Home Reference website. J Med Libr Assoc. 2011 Jan;99(1):70-6. doi: 10.3163/1536-5050.99.1.012.
  • Xu X, Lee DJ, Antani SK, Long LR, Archiband JK. Using Relevance Feedback with Short-term Memory for Content-based Spine X-ray Image Retrieval. J Neurocomputing. June 2009;72(10-12):2259-69.
  • Rondonotti E, Koulaouzidis A, Karargyris A, Giannakou A, Fini L, Soncini M, Pennazio M, Douglas S, Shams A, Lachlan N, Zahid A, Mandelli G, Girelli C. Utility of 3-dimensional image reconstruction in the diagnosis of small-bowel masses in capsule endoscopy (with video). Gastrointest Endosc. 2014 Oct;80(4):642-51. doi: 10.1016/j.gie.2014.04.057. Epub 2014 Jul 3.
  • Antani S, Long LR, Thoma GR, Stanley RJ. Vertebra Shape Classification using MLP for Content-Based Image Retrieval International Neural Networks Society and IEEE Neural Networks Society. 2003 July 2003;:160-65.
  • Ducut E, Liu F, Avila JM, Encinas MA, Diwa M, Fontelo P. Virtual Microscopy in a Developing Country: A Collaborative Approach to Building an Image Library. Journal of eHealth Technology and Application. 2010 Sep;8(2):112-5.
  • 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.
  • Jeronimo J, Massad LS, Schiffman M for the NIH-ASCCP Research Group. Visual Appearance of the Uterine Cervix: Correlation with Human Papillomavirus Detection and Type Am J Obstet Gynecol. 2007 Jul;197(1):47.e1-8
  • Kim I, Rajaraman S, Antani SK. Visual Interpretation of Convolutional Neural Network Predictions in Classifying Medical Image Modalities. Diagnostics (Basel). 2019 Apr 3;9(2). pii: E38. doi: 10.3390/diagnostics9020038.
  • Sarrouti M, Ben Abacha A, Demner-Fushman D. Visual Question Generation from Radiology Images. Proceedings of the First Workshop on Advances in Language and Vision Research.
  • Rajaraman S, Candemir S, Kim I, Thoma GR, Antani SK. Visualization and Interpretation of Convolutional Neural Network Predictions in Detecting Pneumonia in Pediatric Chest Radiographs. Appl. Sci. 2018, 8, 1715.
  • Moorhead R, Johnson C, Munzner T, Pfister H, Rheingans P, Yoo TS. Visualization Corner: Visualization Research Challenges: A Report Summary. IEEE Computing in Science and Engineering. 2006 Jul-Aug;8(4):66-73. DOI: 10.1109/MCSE.2006.77.
  • Munzner T, Johnson C, Moorhead R, Pfister H, Rheingans P, Yoo TS. Visualization Viewpoints: NIH-NSF Visualization Research Challenges Report Summary. IEEE Computer Graphics and Applications. 2006 Mar-Apr;26(2):20-24.

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