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  • Lau JJ, Gayen S, Ben Abacha A, Demner-Fushman D. A dataset of clinically generated visual questions and answers about radiology images. Sci Data. 2018 Nov 20;5:180251. doi: 10.1038/sdata.2018.251.
  • Demner-Fushman D, Antani S, Kalpathy-Cramer J, Müller H. A decade of community-wide efforts in advancing medical image understanding and retrieval. Comput Med Imaging Graph. 2015 Jan;39:1-2. doi: 10.1016/j.compmedimag.2014.12.002.
  • Mao S, Kim J, Thoma G. A Dynamic Feature Generation System for Automated Metadata Extraction in Preservation of Digital Materials Proc. International Workshop on Document Image Analysis for Libraries (DIAL2004). 2004 Jan;: 225-32.
  • Winnenburg R, Bodenreider O. A framework for assessing the consistency of drug classes across sources. J Biomed Semantics. 2014 Jul 9;5:30. doi: 10.1186/2041-1480-5-30. eCollection 2014.
  • Bodenreider O, Burgun A. A framework for comparing phenotype annotations of orthologous genes. Stud Health Technol Inform. 2010;160(Pt 2):1309-13.
  • Lowekamp B, Chen D. A Framework for Improved Regression Testing Based Upon CTest and CDash. The Insight Journal. Web. 2009 Jul-Dec.
  • Nagy DA, Haidegger T, Yaniv Z. A framework for semi-automatic fiducial localization in volumetric images. In: Linte CA, Yaniv Z, Fallavollita P, Abolmaesumi P, Holmes DR III, editors. Augmented Environments for Computer-Assisted Interventions 2014: Proceedings of 9th International AE-CAI Workshop; 2014 Sep 14; Boston. Lecture Notes in Computer Science vol. 8678. Springer; 2014. p. 138-48.
  • Bodenreider O, Peters LB. A graph-based approach to auditing RxNorm. J Biomed Inform. 2009 Jun;42(3):558-70. doi: 10.1016/j.jbi.2009.04.004. Epub 2009 Apr 24.
  • Cameron D, Bodenreider O, Yalamanchili H, Danh T, Vallabhaneni S, Thirunarayan K, Sheth AP, Rindflesch TC. A graph-based recovery and decomposition of Swanson's hypothesis using semantic predications. J Biomed Inform. 2013 Apr;46(2):238-51. doi: 10.1016/j.jbi.2012.09.004. Epub 2012 Sep 28.
  • Kim E, Huang X, Tan G, Long LR, Antani S. A Hierarchical SVG Image Abstraction Layer for Medical Imaging Medical Imaging 2010: Advanced PACS-based Imaging Informatics and Therapeutic Applications. San Diego, California. March 2010;7628
  • Chachra S, Ben Abacha A, Shooshan SE, Rodriguez L, Demner-Fushman D. A Hybrid Approach to Generation of Missing Abstracts in Biomedical Literature. Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers: 1093-1100.
  • Kilicoglu H, Rogers W. A Hybrid System for Extracting Chemical-Disease Relationships from Scientific Literature. 2015. BioCreative 5 Proceedings.
  • Bryant B, Sari-Sarraf H, Long LR, Antani SK. A Kernel Support Vector Machine Trained Using Approximate Global and Exhaustive Local Sampling. Proceedings of the 4th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT) 2017, Austin, Texas, USA, December 2017. Pp. 267-8 DOI: https://doi.org/10.1145/3148055.3149206
  • Rahman MM, Antani SK, Thoma GR. A learning-based similarity fusion and filtering approach for biomedical image retrieval using SVM classification and relevance feedback. IEEE Trans Inf Technol Biomed. 2011 Jul;15(4):640-6. doi: 10.1109/TITB.2011.2151258. Epub 2011 Jun 16.
  • Simpson M, Ford G, Antani S, Demner-Fushman D, Thoma GR. A Lightweight Statistics Package for Interactive Publications Poster at 20th NIH Research Festival (TECH-15), September 2007, National Institutes of Health
  • Krainak DM, Long LR, Thoma GR. A Method of Content-Based Retrieval for a Spinal X-Ray Image Database Proc. of SPIE Medical Imaging: PACS and Integrated Medical Systems. 2002 Feb;4685.
  • Biondich PG, Overhage JM, Dexter PR, Downs SM, Lemmon L, McDonald CJ. A modern optical character recognition system in a real world clinical setting: some accuracy and feasibility observations. Proc AMIA Symp. 2002:56-60.
  • You D, Antani SK, Demner-Fushman D, Thoma GR. A MRF Model for Biomedical Image Segmentation. CBMS 2014. May 2014.
  • Logan RA, Tse T. A Multidiscipline Conceptual Framework for Consumer Health Informatics Stud Health Technol Inform. 2007;129(Pt 2):1169-73
  • Rance B, Doughty E, Demner-Fushman D, Kann MG, Bodenreider O. A mutation-centric approach to identifying pharmacogenomic relations in text. J Biomed Inform. 2012 Oct;45(5):835-41. doi: 10.1016/j.jbi.2012.05.003. Epub 2012 Jun 7.
  • Xu T, Xin C, Long LR, Antani SK, Xue Z, Kim E, Huang X. A New Image Data Set and Benchmark for Cervical Dysplasia Classification Evaluation. Machine Learning in Medical Imaging: 6th International Workshop, MLMI 2015, LNCS 9352, pp. 26–35, 2015. DOI: 10.1007/978-3-319-24888-2 4.
  • Yoo TS, Ackerman MJ. A New Research Program in Medical Image Processing. In: Westwood JD, Hoffman HM, Mogel GT, Robb RA, Stredney D, editors. Stud Health Technol Inform [Studies in Health Technology and Informatics] -- Proceedings of Medicine Meets Virtual Reality 2000;70:385-91. Amsterdam: IOS Press.
  • Cheng B, Stanley RJ, Antani SK, Thoma GR. A Novel Computational Intelligence-based Approach For Medical Image Artifacts Detection Proceedings of the 2010 International Conference on Artificial Intelligence and Pattern Recognition. Orlando, FL. July 2010:113-20
  • Rajaraman S, Candemir S, Xue Z, Alderson P, Kohli M, Abuya J, Thoma GR, Antani SK. A novel stacked generalization of models for improved TB detection in chest radiographs. Proc. IEEE Engineering in Medicine and Biology Conference (EMBC 2018), Honolulu, Hawaii, 2018. pp. 718-721.
  • Rajaraman S, Candemir S, Xue Z, Alderson P, Thoma G, Antani SK. A Novel Stacked Model Ensemble for Improved TB Detection in Chest Radiographs. In Santosh KC et al. (Eds.). Medical Imaging: Artificial Intelligence, Image Recognition, and Machine Learning Techniques. (pp. 1-26). New York, NY: CRC Press, Taylor & Francis Group.

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