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  • 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).
  • Thamizhvani TR, Lakshmanan S, Rajaraman S. Computer Aided Diagnosis of Skin Tumours from Dermal Images. Hemanth D., Smys S. (eds) Computational Vision and Bio Inspired Computing. Lecture Notes in Computational Vision and Biomechanics, vol 28. Springer, Cham
  • 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
  • Cui L, Bodenreider O, Shi J, Zhang GQ. Auditing SNOMED CT hierarchical relations based on lexical features of concepts in non-lattice subgraphs. Biomed Inform. 2018 Feb;78:177-184. doi: 10.1016/j.jbi.2017.12.010. Epub 2017 Dec 20.
  • Poostchi M, Silamut K, Maude RJ, Jaeger S, Thoma GR. Image analysis and machine learning for detecting malaria. Transl Res. 2018 Apr;194:36-55. doi: 10.1016/j.trsl.2017.12.004. Epub 2018 Jan 12.
  • 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.
  • Harpaz R, DuMouchel W, Schuemie M, Bodenreider O, Friedman C, Horvitz E, Ripple A, Sorbello A, White RW, Winnenburg R, Shah NH. Toward multimodal signal detection of adverse drug reactions. J Biomed Inform. 2017 Dec;76:41-49. doi: 10.1016/j.jbi.2017.10.013. Epub 2017 Nov 1.
  • 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
  • Abhyankar S, Schluter P, Bennett K, Vreeman D, McDonald CJ. Enabling Interoperability between Healthcare Devices and EHR Systems. In 2017 AMIA Symposium. Wasington DC: IEEE.
  • McDonald CJ, Vreeman D, Wang K, Carr C, Colins B, Abhyankar S, Deckard J, Rubin D, Langlotz C. The LOINC/RSNA Radiology Playbook: A unified terminology for radiology procedures. . In 2017 AMIA Symposium. Washington DC.
  • 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.
  • Kury F, Baik SH, McDonald CJ. Cardioprotective Drugs and Incident Dementias in Medicare's Big Data. AMIA 2017.
  • Chatain GP, Patronas N, Smirniotopoulos J, James G, Piazza M, Benzo S, Ray-Chaudrury A, Sharma S, Lodish M, Nieman L, Stratakis CA, Chittiboina P. Potential utility of FLAIR in MRI-negative Cushing's disease. J Neurosurg. 2017 Oct 13:1-9. doi: 10.3171/2017.4.JNS17234.
  • Fung K, Gutierrez A, Ameye F, D’Have A, Ariel B. Demonstrating the Benefits of Mapping SNOMED CT to ICD-10-PCS through a Prototype Application for End User Implementation. SNOMED Expo Oct 2017, Bratislava, Slovakia pp. 0
  • 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.
  • Coakley M, Hurt D, Weder N, Mtingwa M, Fincher EC, Alekseyev V, Chen D, Yun A, Gizaw M, Swan J, Yoo TS, Huyen Y. The NIH 3D Print Exchange: A Public Resource for Bioscientific and Biomedical 3D Prints 3D Print Additive Manufacturing, Sep. 1, 2014, 1(3):137-140.
  • Sun H, Li J, Wu Y, Wang L, Fung K. Using an Ontology-Based Approach to Handle Author Affiliations in a Large Biomedical Citation Database. Stud Health Technol Inform. 2017;245:1338.
  • Raje S, Bodenreider O. Interoperability of disease concepts in clinical and research ontologies – Contrasting coverage and structure in the Disease Ontology and SNOMED CT. Stud Health Technol Inform. 2017;245:925-929.
  • 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.

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