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  • 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.
  • Mao S, Nie L, Thoma GR. Unsupervised Style Classification of Document Page Images Proc IEEE International Conference on Image Processing, September 2005, Genova, Italy; Vol. II: 510-13
  • Misra D, Thoma GR. Use of descriptive metadata as a knowledgebase for analyzing data in large textual collections. Proc. IS&T Archiving 2013. Washington D.C. Proc. IS&T Archiving 2013. Washington D.C. pg 193-199.
  • Long LR, Thoma GR. Use of Shape Models to Search Digitized Spine X-Rays IEEE Computer-Based Medical Systems. 2000 June;: 255-60.
  • 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
  • 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
  • Abhyankar S, Callaghan FM, Demner-Fushman D, McDonald CJ. Using informatics tools to study obesity and outcomes after critical illness. NLM Informatics Training Conference 2011, National Institutes of Health (NIH) Campus, Natcher Conference Center, Bethesda, MD, June 28-30, 2011.
  • 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.
  • Hauser SE, Demner-Fushman D, Jacobs JL, Humphrey SM, Ford G, Thoma GR. Using Wireless Handheld Computers to Seek Information at the Point of Care: An Evaluation by Clinicians. J Am Med Inform Assoc. 2007 Nov-Dec;14(6):807-15. Epub 2007 Aug 21.
  • 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.
  • 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.
  • 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.
  • Rajaraman S, Antani SK. Visualizing Salient Network Activations in Convolutional Neural Networks for Medical Image Modality Classification. Santosh K., Hegadi R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1036. Springer, Singapore
  • Ben Abacha A, Hasan SA, Datls W, Liu J, Demner-Fushman D, Muller H. VQA-Med: Overview of the medical visual question answering task at imageclef 2019. CEUR Workshop Proceedings, 9-12, 2019.
  • Rajaraman S, Antani SK. Weakly Labeled Data Augmentation for Deep Learning: A Study on COVID-19 Detection in Chest X-Rays. Diagnostics 2020, 10, 358.
  • Lingappa G, Thoma GR, Antani SK. Web Interface: MyMorph

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