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  • 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.
  • Ganesan P, Xue Z, Singh S, Long LR, Ghoraani B, Antani SK. Performance Evaluation of a Generative Adversarial Network for Deblurring Mobile-phone Cervical Images. Proc. IEEE Engineering in Medicine and Biology Conference (EMBC), Berlin, Germany, 23 – 27 July 2019. pp. 4487 – 4490.
  • 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.
  • 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.
  • 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.
  • Candemir S, Rajaraman S, Thoma GR, Antani SK. Deep Learning for Grading Cardiomegaly Severity in Chest X-rays: An Investigation. Proc. IEEE Life Sciences Conference (LSC 2018), Montreal, Quebec, Canada, 28 – 30 October 2018. pp. 109-113.
  • Moallem G, Sari-Sarraf H, Poostchi Mohammadabadi M, Maude R, Silamut K, Antani SK, Jaeger S. Detecting and segmenting overlapping red blood cells in microscopic images of thin blood smears. SPIE Medical Imaging, 2018.
  • Ben Abacha A, Gayen S, Lau JJ, Rajaraman S, Demner-Fushman D. NLM at ImageCLEF 2018 Visual Question Answering in the Medical Domain. CLEF2018 Working Notes. CEUR Workshop Proceedings, Avignon, France, CEUR-WS.org (September 10-14 2018).
  • Rae A, Kim J, Le DX, Thoma GR. Main Content Detection in HTML Journal Articles. DocEng ’18: ACM Symposium on Document Engineering 2018, August 28–31, 2018, Halifax, NS, Canada. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3209280.3229115
  • 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.
  • Xue Z, Long LR, Jaeger S, Folio L, Thoma GR. Extraction of Aortic Knuckle Contour in Chest Radiographs Using Deep Learning. EMBC 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.
  • Xue Z, Rajaraman S, Long LR, Antani SK, Thoma GR. Gender Detection from Spine X-ray Images Using Deep Learning. Proc. IEEE International Symposium on Computer-Based Medical Systems (CBMS), Karlstad, Sweden, 2018. pp. 54-58, DOI:10.1109/CBMS.2018.00017.
  • 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, 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.
  • Xue Z, Jaeger S, Antani SK, Long LR, Karargyris A, Siegelman J, Folio L, Thoma GR. Localizing tuberculosis in chest radiographs with deep learning. Proc SPIE 10579, Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications, 105790U (6 March 2018) pp. doi: 10.1117/12.2293022
  • 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.
  • Zohora FT, Antani SK, Santosh KC. Circle-like foreign element detection in chest x-rays using normalized cross-correlation and unsupervised clustering. Proc. SPIE 10574, Medical Imaging 2018: Image Processing, 105741V (2 March 2018); doi: 10.1117/12.2293739; doi.org/10.1117/12.2293739.
  • Rajaraman S, Antani SK, Candemir S, Xue Z, Abuya J, Kohli M, Alderson P, Thoma GR. Comparing deep learning models for population screening using chest radiography. Proc. SPIE 10575, Medical Imaging 2018: Computer-Aided Diagnosis, 105751E (27 February 2018).
  • Xue Z, Jaeger S, Antani SK, Long LR, Karargyris A, Siegelman J, Folio LR, Thoma GR. Localizing tuberculosis in chest radiographs with deep learning. SPIE Medical Imaging 2018
  • Xue Z, Antani SK, Long LR, Thoma GR. Using deep learning for detecting gender in adult chest radiographs. SPIE Medical Imaging 2018
  • 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
  • de Herrera G, Long LR, Antani SK. Graph Representation for Content–based fMRI Activation Map Retrieval. Proceedings of 1st Life Sciences Conference, Sydney, Australia, December 2017 pp. 129-32 DOI: https://doi.org/10.1109/LSC.2017.8268160.
  • 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.
  • Zou J, Antani SK, Thoma GR. Localizing and Recognizing Labels for Multi-Panel Figures in Biomedical Journals. Proceedings of International Conference on Document Analysis and Recognition, November 13, 2017
  • Almubarak HA, Stanley RJ, Long LR, Antani SK, Thoma GR, Zuna R, Frazier SR. Convolutional Neural Network Based Localized Classification of Uterine Cervical Cancer Digital Histology Images. Procedia Computer Science, Volume 114, 2017, Pages 281-287, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2017.09.044.
  • Ekong DU, Fontelo P. Prototype telepathology solutions that use the Raspberry Pi and mobile devices. 2017 IEEE Global Humanitarian Technology Conference (GHTC), San Jose CA, 2017: 1-4.
  • 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.
  • 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.
  • 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
  • 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 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.
  • Candemir S, Antani SK, Xue Z, Thoma GR. Novel Method for Storyboarding Biomedical Videos for Medical Informatics. 30th IEEE International Symposium on Computer-Based Medical Systems
  • Ding M, Antani SK, Jaeger S, Xue Z, Candemir S, Kohli M, Thoma GR. Local-Global Classifier Fusion for Screening Chest Radiographs. Proc. SPIE 10138, Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications, 101380A (March 13, 2017); doi:10.1117/12.2252459
  • Xue Z, Antani SK, Long LR, Thoma GR. Automatic multi-label annotation of abdominal CT images using CBIR. Proc. SPIE 10138, Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications, 1013807 (March 13, 2017); doi:10.1117/12.2254368.
  • Kury F, Baik SH, McDonald CJ. Analysis of Healthcare Cost and Utilization in the First Two Years of the Medicare Shared Savings Program Using Big Data from the CMS Enclave. AMIA Annu Symp Proc. 2017 Feb 10;2016:724-733. eCollection 2016.
  • 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.
  • De Herrera A, Long LR, Antani SK. Content-Based fMRI Brain Maps Retrieval. International Conference on Brain and Health Informatics, Omaha, NE, USA, October 13-16, 2016.
  • 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
  • Ben Abacha A, de Herrera A, Wang Ke, Long LR, Antani SK, Demner-Fushman D. Named entity recognition in functional neuroimaging literature. 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Kansas City, MO, 2017, pp. 2218-2220.
  • Liang Z, Powell A, Ersoy I, Poostchi M, Silamut K, Palaniappan K, Guo P, Hossain M, Antani SK, Maude R, Huang J, Jaeger S, Thoma GR. CNN-Based Image Analysis for Malaria Diagnosis. IEEE International Conference on Bioinformatics & Biomedicine (BIBM), Shenzhen, China, 2016.
  • Kochmann M, Locatis CN. Telemedicine in the Apple App Store: An exploratory study of teledermatology apps. In Smari, W. & Natarian, J. (Eds.), Proc 2016 Int Conf Collaboration Technologies and Systems, Orlando, Florida, October 31-November 4, Institute for Electrical and Electronic Engineers & Association for Computing Machinery, 534-537.
  • Marchell R, Locatis CN, Ackerman MA. High definition live interactive and store and forward teledermatology: A comparison of concordance, confidence, and satisfaction with in-person exams. In Smari, W. & Natarian, J. (Eds.), Proceedings of the 2016 International Conference on Collaboration Technologies and Systems, Orlando, Florida, October 31. Institute for Electrical and Electronic Engineers & Association for Computing Machinery, 520-523.
  • Xue Z, Rahman M, Antani SK, Long LR, Demner-Fushman D, Thoma GR. Modality Classification for Searching Figures in Biomedical Literature. Proceedings of the IEEE 29th International Symposium on Computer-Based Medical Systems, pp. 152-157, 2016. doi:10.1109/CBMS.2016.29.
  • 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.
  • 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.
  • Shin HC, Roberts K, Lu L, Demner-Fushman D. Learning to Read Chest X-Rays: Recurrent Neural Cascade Model for Automated Image Annotation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 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.
  • Xue Z, Antani SK, Long LR, Demner-Fushman D, Thoma GR. Improving face image extraction by using deep learning technique. Proc. SPIE 9789, Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and Innovations, 97890J (March 25, 2016); doi:10.1117/12.2216278.

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