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  • 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.
  • KC S, Vajda S, Antani SK, Thoma GR. Automatic Pulmonary Abnormality Screening using Thoracic Edge Map. IEEE, 28th International Symposium on Computer-Based Medical Systems (CBMS), pp. 360-361, 2015.
  • 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.
  • KC S, Xue Z, Antani SK, Thoma GR. NLM at ImageCLEF 2015: Biomedical Multipanel Figure Separation. Editors: Cappellato, L., Ferro, N., Jones, G., and San Juan, E., CLEF 2015 Labs and Workshops, Notebook Papers. CEUR WorkshopProceedings (CEUR-WS.org), ISSN 1613-0073, http://ceur-ws.org/ Vol-1391/.
  • KC S, Wendling L, Antani SK, Thoma GR. Scalable arrow detection in biomedical images. Pattern Recognition (ICPR), 2014 22nd International Conference; pp 3257-62. DOI: 10.1109/ICPR.2014.561
  • KC S, Candemir S, Jaeger S, Folio L, Karargyris A, Antani SK, Thoma GR. Rotation detection in chest radiographs based on generalized line histogram of rib-orientations. IEEE 27th International Symposium on Computer-Based Medical Systems, New York, NY, USA, May 27-29, 2014: page 138-142.
  • 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
  • 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 I, Thoma GR. Machine Learning with Selective Word Statistics for Automated Classification of Citation Subjectivity in Online Biomedical Articles. Proc. Int’l Conf. Artificial Intelligence (ICAI’17), pp. 201-207, Las Vegas, July 2017.
  • 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. Identifying “comment-on” citation data in online biomedical articles using SVM-based text summarization technique. Proc. Int’l Conf. Artificial Intelligence (ICAI’12), vol. 1, pp. 431-437, Las Vegas, July 2012.
  • 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, 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 IC, Le DX, Thoma GR. Hybrid approach combining contextual and statistical information for identifying and statistical information for identifying MEDLINE citation terms. Proc. SPIE-IS/T Electronic Imaging. San Jose, CA. January 2008;6815:68150P(1-9)
  • Kim IC, Le DX, Thoma GR. Identification of "comment-on sentences" in online biomedical documents using support vector machines. Proc. SPIE conference on Document Recognition and Retrieval, 6500:65000O (1-8), San Jose, January 2007.
  • Kim J, Tran L, Chew E, Antani SK. Optic Disc and Cup Segmentation for Glaucoma Characterization Using Deep Learning 2019 IEEE 32th International Symposium on Computer-Based Medical Systems (CBMS), pp 489-494, Cordoba, Spain, June 2019.
  • Kim J, Tran L, Chew E, Antani SK, Thoma GR. Optic Disc Segmentation in Fundus Images Using Deep Learning. SPIE Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications, Vol. 10954, San Diego, USA, February 2019.
  • Kim J, Candemir S, Chew E, Thoma GR. Region of Interest Detection in Fundus Images Using Deep Learning and Blood Vessel Information. The 31th IEEE International Symposium on Computer-Based Medical Systems. (IEEE CBMS 2018), pp. 357-362, Karlstad, Sweden, June 2018.
  • Kim J, Hong S, Thoma GR. Labeling Author Affiliations in Biomedical Articles Using Markov Model Classifiers. The 13th International Conference on Data Mining (DMIN2017), pp. 105-110, Las Vegas, USA, July 2017.
  • Kim J, Thoma GR. Named Entity Recognition in Affiliations of Biomedical Articles Using Statistics and HMM Classifiers. The 2016 International Conference on Data Mining (DMIN2016), Las Vegas, USA, pp. 236-241, July, 2016.
  • 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.
  • Kim J, Le DX, Thoma GR. Identification of Investigator Name Zones Using SVM Classifiers and Heuristic Rules. 12th international Conference on Document Analysis and Recognition (ICDAR). Washington D.C., August 2013.
  • Kim J, Le DX, Thoma GR. Combining SVM Classifiers to Identify Investigator Name Zones in Biomedical Articles. IS&T/SPIE’s 22nd Annual Symposium on Electronic Imaging. San Francisco, CA, January 2012; 8297.
  • Kim J, Le DX, Thoma GR. Naive Bayes and SVM Classifiers For Classifying Databank Accession Number Sentences From Online Biomedical Articles IS&T/SPIE's 22nd Annual Symposium on Electronic Imaging. San Jose, CA. January 2010;7534:75340U-1 - 8

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