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  • Roberts K, Demner-Fushman D. Toward a Natural Language Interface for EHR Questions. AMIA Jt Summits Transl Sci Proc. 2015 Mar 25;2015:157-61. eCollection 2015.
  • Kilicoglu H, Demner-Fushman D, Rindflesch TC, Wilczynski NL, Haynes RB. Toward Automatic Recognition of High Quality Clinical Evidence. AMIA Annu Symp Proc. 2008 Nov 6:368
  • Kilicoglu H, Demner-Fushman D, Rindflesch TC, Wilczynski NL, Haynes RB. Towards Automatic Recognition of Scientifically Rigorous Clinical Research Evidence J Am Med Inform Assoc. 2009 Jan-Feb;16(1):25-31. Epub 2008 Oct 24.
  • Nishinaga N, Tatsumi H, Gill M, Akashib A, Nogawa H, Reategui I. Trans-Pacific Demonstration of Visible Human Space Communications. 2002 March; 17(4):303-311.
  • Goedert JJ, Scoppio BM, Pfeiffer R, Neve L, Federici AB, Long LR, Dolan BM, Brambati M, Bellinvia M, Lauria C, Preiss L, Boneschi V, Whitby D, Brambilla L. Treatment of classic Kaposi sarcoma with a nicotine dermal patch: a phase II clinical trial. phase II clinical trial. J Eur Acad Dermatol Venereol. 2008 Sep;22(9):1101-9. doi: 10.1111/j.1468-3083.2008.02720.x. Epub 2008 Apr 1.r 1.
  • Jaeger S, Antani S, Thoma GR. Tuberculosis Screening of Chest Radiographs. 2 June 2011, SPIE Newsroom. DOI: 10.1117/2.1201105.003732i.
  • Jaeger S, Candemir S, Antani SK, Wang Y, Lu P, Thoma GR. Two public chest X-ray datasets for computer-aided screening of pulmonary diseases. Quant Imaging Med Surg. 2014 Dec;4(6):475-7. doi: 10.3978/j.issn.2223-4292.2014.11.20.
  • Demner-Fushman D, Mork JG, Shooshan SE, Aronson AR. UMLS content views appropriate for NLP processing of the biomedical literature vs. clinical text. J Biomed Inform. 2010 Aug;43(4):587-94. doi: 10.1016/j.jbi.2010.02.005. Epub 2010 Feb 10.
  • Datta S, Rodriguez L, Shooshan SE, Demner-Fushman D, Roberts K. Understanding Spatial Language in Radiology: Representation Framework, Annotation, and Spatial Relation Extraction from Chest X-ray Reports using Deep Learning. Journal of Biomedical Informatics, 103473.
  • Datta S, Si Y, Rodriguez L, Shooshan S, Demner-Fushman D, roberts K. Understanding Spatial Language in Radiology: Representation Framework, Annotation, and Spatial Relation Extraction from Chest X-ray Reports using Deep Learning. arXiv preprint arXiv:1908.04485, 2019.
  • Rajaraman S, Silamut K, Hossain MA, Ersoy I, Maude RJ, Jaeger S, Thoma GR, Antani SK. Understanding the learned behavior of customized convolutional neural networks toward malaria parasite detection in thin blood smear images. J Med Imaging (Bellingham). 2018 Jul;5(3):034501. doi: 10.1117/1.JMI.5.3.034501. Epub 2018 Jul 18.
  • 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]
  • 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
  • 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.
  • 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.
  • 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.
  • 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.

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