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  • 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.
  • Antani SK, You D, Simpson M, Rahman M, Demner-Fushman D, Thoma GR. The role of image modality and visual characteristics in archiving biomedical images. Proc of IS&T Archiving Conference. Volume 2013, Number 1, 2013, pp. 31-35.
  • Lin J, Demner-Fushman D. The Role of Knowledge in Conceptual Retrieval: A Study in the Domain of Clinical Medicine Proc SIGIR 2006, pages 99-106, August 2006, Seattle, Washington
  • Pearson G, Gill MJ, Antani SK, Neve L, Miernicki G, Phichaphop K, Kanduru A, Jaeger S, Thoma GR. The Role of Location For Family Reunification During Disasters. HealthGIS 2012. Redondo Beach, CA. November 2012.
  • 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
  • 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
  • Simpson MS, You D, Rahman MM, Antani SK, Thoma GR, Demner-Fushman D. Towards the creation of a visual ontology of biomedical imaging entities. AMIA Annu Symp Proc. 2012;2012:866-75. Epub 2012 Nov 3.
  • Antani SK. Tuberculosis Chest X-ray Image Data Sets
  • 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
  • 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.
  • 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.
  • Lingappa G, Thoma GR, Antani SK. Web Interface: MyMorph

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