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  • Lin J, Demner-Fushman D. "Bag of words" is not enough for strength of evidence classification AMIA Annu Symp Proc. 2005:1031.
  • Jimeno-Yepes A, Wilkowski B, Mork J, van Lenten E, Demner-Fushman D, Aronson AR. A bottom-up approach to MEDLINE indexing recommendations. AMIA Annu Symp Proc. 2011;2011:1583-92. Epub 2011 Oct 22.
  • Rahman MM, Antani SK, Thoma GR. A Classification-Driven Similarity Matching Framework For Retrieval of Biomedical Images. 11th ACM International Conference on Multimedia Information Retrieval (MIR 2010). 2010:147-154.
  • You D, Antani SK, Demner-Fushman D, Thoma GR. A Contour-based Shape Descriptor For Biomedical Image Classification and Retrieval. Proceedings of SPIE 2014, Vol. 9021, Document Recognition and Retrieval XXI. February 2014;9021.
  • 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.
  • 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
  • Karargyris A, Bourbakis N. A methodology for detecting blood-based abnormalities in wireless capsule endoscopy videos. BioInformatics and BioEngineering, 2008. BIBE 2008. 8th IEEE International Conference. 2008 Oct 8; pp 1-6. doi: 10.1109/BIBE.2008.4696806.
  • You D, Antani SK, Demner-Fushman D, Thoma GR. A MRF Model for Biomedical Image Segmentation. CBMS 2014. May 2014.
  • 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.
  • 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.
  • Tulpule B, Hernes DL, Srinivasan Y, Mitra S, Sriraja Y, Nutter BS, Phillips B, Long RL, Ferris DG. A Probabilistic Approach to Segmentation and Classification of Neoplasia in Uterine Cervix Images Using Color and Geometric Features SPIE Medical Imaging, February 2005; San Diego, CA; vol. 5748:995-1003
  • Demner-Fushman D, Seckman C, Fisher C, Hauser SE, Clayton J, Thoma GR. A prototype system to support evidence-based practice AMIA Annu Symp Proc. 2008 Nov 6:151-5.
  • You D, Simpson M, Antani SK, Demner-Fushman D, Thoma GR. A robust pointer segmentation in biomedical images toward building a visual ontology for biomedical article retrieval. Proc. SPIE 8658, Document Recognition and Retrieval XX, 86580Q (February 4, 2013); doi:10.1117/12.2005934.
  • Zhang X, Zou J, Le DX, Thoma GR. A Semi-supervised Learning Method to Classify Grant Support Zone in Web-based Medical Articles Proc SPIE Electronic Imaging Science and Technology, Document Recognition and Retrieval. January 2009;7247:7247 OW(1-8)
  • Abhyankar S, Demner-Fushman D. A simple method to extract key maternal data from neonatal clinical notes. AMIA Annu Symp Proc. 2013 Nov 16;2013:2-9. eCollection 2013.
  • Zhang X, Zou J, Le DX, Thoma GR. A Stacked Sequential Learning Method For Investigator Name Recognition From Web-based Medical Articles 17th Document Recognition and Retrieval Conference (SPIE-DR&R). San Jose, CA. January 2010;7534:753404-7
  • Rahman MM, Antani SK, Demner-Fushman D, Thoma GR. A visual concept-based interactive biomedical image retrieval using entropy and spatial information. Proc. SPIE. 9418, Medical Imaging 2015: PACS and Imaging Informatics: Next Generation and Innovations, 94180U. (March 17, 2015) doi: 10.1117/12.2081456.
  • Xue Z, Long R, Antani SK, Thoma GR. A Web-accessible Content-based Cervicographic Image Retrieval System Proc SPIE Medical Imaging 2008. April 2008;6919:691907-1-9
  • Mrabet Y, Vougiouklis P, Kilicoglu H, Gardent C, Demner-Fushman D, Hare J, Simperl E. Aligning Texts and Knowledge Bases with Semantic Sentence Simplification. WebNLG 2016.
  • Kilicoglu H, Fiszman M, Roberts K, Demner-Fushman D. An Ensemble Method for Spelling Correction in Consumer Health Questions. AMIA Annu Symp Proc. 2015 Nov 5;2015:727-36. eCollection 2015.
  • Pearson G, Gill MJ. An Evaluation of Motion JPEG 2000 for Video Archiving. Proc. Archiving 2005. Washington, D.C. April 2005:237-43.
  • Jaeger S. An information-theoretic neural model based on concepts in Chinese medicine. 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW).
  • Rahman MM, You D, Simpson M. An interactive image retrieval framework for biomedical articles based on visual region-of-interest (ROI) identification and classification [Abstract]. The 2nd IEEE Conference on Healthcare Informatics, Imaging, and Systems Biology Analyzing Big Data for Healthcare and Biomedical Sciences (HISB 2012). La Jolla, CA. September 2012.
  • Xue Z, Antani SK, Long LR, Thoma GR. An online segmentation tool for cervicographic image analysis. ACM International Health Informatics Symposium, IHI 2010, Arlington, VA, USA, November 11 - 12, 2010, Proceedings; 01/2010.
  • Callaghan F, Jackson MT, Demner-Fushman D, Abhyankar S, McDonald C. Analysis of data that has been extracted from free-text using natural language processing: a likelihood model for misclassification with an application to medical informatics. International Conference on Advances in Interdisciplinary Statistics and Combinatorics (AISC2012), Greensboro, NC, October 2012
  • You D, Simpson M, Antani SK, Demner-Fushman D, Thoma GR. Annotating image ROIs with text descriptions for multimodal biomedical document retrieval. Proc. SPIE 8658, Document Recognition and Retrieval XX, 86580Q (February 4, 2013); doi:10.1117/12.2005934; http://dx.doi.org/10.1117/12.2005934.
  • Roberts K, Demner-Fushman D. Annotating Logical Forms for EHR Questions. Proceedings of the Language Resources and Evaluation Conference, LREC,23-28 May 2016, Portorož.
  • Kilicoglu H, Ben Abacha A, Mrabet Y, Roberts K, Rodriguez L, Shooshan SE, Demner-Fushman D. Annotating named entities in consumer health questions. LREC,23-28 May 2016, Portorož.
  • Roberts K, Masterton K, Kilicoglu H, Fiszman M, Demner-Fushman D. Annotating Question Decomposition on Complex Medical Questions. LREC 2014.
  • Roberts K, Masterton K, Fiszman M, Kilicoglu H, Demner-Fushman D. Annotating Question Types for Consumer Health Questions. LREC 2014, BioTxtM workshop.
  • Demner-Fushman D, Shooshan SE, Rodriguez L, Antani SK, Thoma GR. Annotation of Chest Radiology Reports for Indexing and Retrieval. Multimodal Retrieval in the Medical Domain 2015 (MRMD 2015), Vienna, Austria, March 29, 2015
  • Demner-Fushman D, Lin J. Answer Extraction, Semantic Clustering, and Extractive Summarization for Clinical Question Answering Proc COLING/ACL 2006. July 2006, Sydney, Australia
  • Gandhi T, Kasturi R, Antani S. Application of Planar Motion Segmentation for Scene Text Extraction Proc. of the 15th IEEE International Conference of Pattern Recognition. 2000 Sept.;1:1831-4.
  • Guan Y, Li M, Jaeger S, Lure F, Raptopoulos V, Lu P, Folio LR, Candemir S, Antani SK, Siegelman J, Li J, Wu T, Thoma GR, Qu S. Applying Artificial Intelligence and Radiomics for Computer Aided Diagnosis and Risk Assessment in Chest Radiographs. 2nd Conference on Machine Intelligence in Medical Imaging (CMIMI) of the Society for Imaging Informatics in Medicine (SIIM), Poster, 2017.
  • Misra D, Mao S, Rees J, Thoma GR. Archiving a Historic Medico-legal Collection: Automation and Workflow Customization Proc IS&T Archiving 2007. Arlington, Virginia, May 2007; 157-61
  • KC S, Naved A, Roy PP, Wendling L, Antani SK, Thoma GR. Arrowhead detection in biomedical images. Proceedings IS&T Electronic Imaging, Document Recognition and Retrieval XXIII, 2016, pp. 1-7.
  • Rajaraman S, Sornapudi S, Kohli M, Antani SK. Assessment of an ensemble of machine learning models toward abnormality detection in chest radiographs. Proc. IEEE Engineering in Medicine and Biology Conference (EMBC), Berlin, Germany, 23 – 27 July 2019. pp. 3689 – 3692.
  • Ganesan P, Rajaraman S, Long LR, Ghoraani B, Antani SK. Assessment of Data Augmentation Strategies Toward Performance Improvement of Abnormality Classification in Chest Radiographs. Proc. IEEE Engineering in Medicine and Biology Conference (EMBC), Berlin, Germany, 23 – 27 July 2019. pp. 841 – 844.
  • Kim I, Thoma GR. Automated Classification of Author’s Sentiments in Citation Using Machine Learning Techniques: A Preliminary Study. Proc. the 2015 IEEE Conf. Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2015), Niagara Falls, Canada, Aug. 12-15, 2015.
  • Kim I, Le DX, Thoma GR. Automated Cleanup Processing for Extracting Bibliographic Data from Biomedical Online Journals In: Callaos N, Lesso W, editors. SCI 2005. Proc. 9th World Multiconference on Systemics, Cybernetics and Informatics; 2005 Jul 10-13; Vol. 4; Orlando (FL): International Institute of Informatics and Systemics; c2005. 401-5
  • Kim I, Le DX, Thoma GR. Automated identification of biomedical article type using support vector machines. Proc. 18th SPIE Document Recognition and Retrieval, 7874:787403 (1-9), San Francisco, January 2011.
  • Kim I, Thoma GR. Automated Identification of Potential Conflict-of-Interest in Biomedical Articles Using Hybrid Deep Neural Network. Proc. 14th Int’l Conf. Machine Learning and Data Mining (MLDM 2018), LNAI 10934, pp. 99-112, Newark, NJ, July 2018.
  • Kim I, Thoma GR. Automated Identification of Potential Conflict-of-Interest in Biomedical Articles Using Hybrid Deep Neural Network. Proc. 14th Int’l Conf. Machine Learning and Data Mining (MLDM 2018), LNAI 10934, pp. 99-112, Newark, NJ, July 2018.
  • Kim J, Le DX, Thoma GR. Automated Labeling Of Biomedical Online Journal Articles In: Callaos N, Lesso W, editors. SCI 2005. Proc 9th World Multiconference on Systemics, Cybernetics and Informatics; 2005 Jul 10-13; Vol. 4; Orlando (FL): International Institute of Informatics and Systemics; c2005. 406-11
  • Thoma GR, Mao S, Misra D. Automated Metadata Extraction to Preserve the Digital Contents of Biomedical Collections Proc VIIP 2005. September 2005. Benidorm, Spain; 214-19
  • Hauser SE, Le DX, Thoma GR. Automated Zone Correction in Bitmapped Document Images SPIE: Document Recognition and Retrieval VII. 2000 Jan;3976: 248-58.
  • Rodriguez LM, Fushman DD. Automatic Classification of Structured Product Labels for Pregnancy Risk Drug Categories, a Machine Learning Approach. AMIA Annu Symp Proc. 2015 Nov 5;2015:1093-102. eCollection 2015.
  • Lotenberg S, Gordon S, Long LR, Antani SK, Jeronimo J, Greenspan H. Automatic Evaluation of Uterine Cervix Segmentations Proc. SPIE Medical Imaging 2007. Vol. 6515: 65151J-1-12.

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