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  • Neve L, Long LR, Antani SK. Software: Boundary Marking Tool 2 (BMT2)
  • Thoma GR, Ford G, Demner-Fushman D, Antani SK, Chung M. Software: Panorama
  • Xue Z, Long LR, Antani SK, Thoma GR. Spine x-ray image retrieval using partial vertebral boundaries. 24th International Symposium on Computer-Based Medical Systems. Bristol, UK. June 2011.
  • KC S, Antani SK, Thoma GR. Stitched Multipanel Biomedical Figure Separation. IEEE, 28th International Symposium on Computer-Based Medical Systems (CBMS), pp. 54-59, 2015.
  • Zou J, Le DX, Thoma GR. Structure and Content Analysis for HTML Medical Articles: A Hidden Markov Model Approach Proc August 2007 ACM Symposium on Document Engineering. pp. 199-201
  • Long RL, Antani S, Jeronimo J, Schiffman M, Bopf M, Neve L, Cornwall C, Budihas SC, Thoma GR. Technology for Medical Education, Research, and Disease Screening by Exploitation of Biomarkers in a Large Collection of Uterine Cervix Images Proc CBMS 2006, June 2006, Salt Lake City, Utah; 826-31
  • Misra D, Seamans J, Thoma GR. Testing the Scalability of a DSpace-based Archive Proc. IS&T Archiving 2008. Bern, Switzerland. June 2008:36-40
  • You D, Rahman MM, Antani SK, Demner-Fushman D, Thoma GR. Text- and content-based biomedical image modality classification. Proc. SPIE Medical Imaging. Orlando, FL. February 2013;8674-21.
  • Mrabet Y, Kilicoglu H, Demner-Fushman D. TextFlow: A Text Similarity Measure based on Continuous Sequences. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017, Vancouver, Canada, July 30 - August 4, Volume
  • Overby CL, Tarczy-Hornoch P, Demner-Fushman D. The potential for automated question answering in the context of genomic medicine: An assessment of existing resources and properties of answers Summit on Translat Bioinforma. 2009 Mar 1;2009:1-25.
  • Demner-Fushman D, Hauser SE, Thoma GR. The role of title, metadata and abstract in identifying clinically relevant journal articles. AMIA Annu Symp Proc. 2005:191-5.
  • Huang X, Wang W, Xue Z, Antani SK, Long LR, Jeronimo J. Tissue Classification using Cluster Features for Lesion Detection in Digital Cervigrams Proc. SPIE Medical Imaging 2008. April 2008;6914:69141Z-1-8
  • Rodriguez L, Morrison SM, Greenberg K, Demner-Fushman D. Towards Automatic Discovery of Genes Related to Human Placenta [Poster]. Poster Fall AMIA 2016.
  • Antani SK. Tuberculosis Chest X-ray Image Data Sets
  • 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.
  • 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.

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