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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
  • Zweigenbaum P, Demner-Fushman D. Advanced Literature-Mining Tools. In Edwards D, Stajich J, and Hansen D. (Editors). Bioinformatics: Tools and Applications. Springer 2009.
  • Demner-Fushman D. A dataset of 200 structured product labels annotated for adverse drug reactions. Sci Data. 2018 Jan 30;5:180001. doi: 10.1038/sdata.2018.1.
  • 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.
  • Kayaalp M. Patient Privacy in the Era of Big Data. Balkan Med J. 2018 Jan 20;35(1):8-17. doi: 10.4274/balkanmedj.2017.0966. Epub 2017 Sep 13.
  • 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.
  • Ben Abacha A, Long LR, Seco de Herrera AG, Antani SK, Wang K, Demner-Fushman D. Named Entity Recognition in Functional Neuroimaging Literature. BIBM 2017
  • Lu C, Tormey D, McCreedy L, Browne AC. Enhancing LexSynonym Features in the Lexical Tools AMIA 2017 Annual Symposium, Washington, DC, November 04-08, 2017, p. 2090
  • 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.
  • 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.
  • 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.
  • Roberts K, Gururaj A, Chen X, Pournejati S, Cohen T, Hersh WR, Demner-Fushman D. Information Retrieval for Biomedical Datasets. 2016 bioCADDIE Challenge. AMIA 2017.
  • Bhupatiraju R, Fung K, Bodenreider O. MetaMapLite in Excel: Biomedical named-entity recognition for non-technical users. Stud Health Technol Inform (Proc Medinfo): 1252.
  • 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.
  • Blake C, Rindflesch TC. Leveraging syntax to better capture the semantics of elliptical coordinated compound noun phrases. J Biomed Inform. 2017 Aug;72:120-131. doi: 10.1016/j.jbi.2017.07.001. Epub 2017 Jul 4.
  • Kilicoglu H, Rosemblat G, Rindflesch TC. Assigning factuality values to semantic relations extracted from biomedical research literature. PLoS One. 2017 Jul 5;12(7):e0179926. doi: 10.1371/journal.pone.0179926. eCollection 2017.
  • Rindflesch TC, Blake CL, Fiszman M, Kilicoglu H, Rosemblat G, Schneider J, Zeiss CJ. Informatics Support for Basic Research in Biomedicine. ILAR J. 2017 Jul 1;58(1):80-89. doi: 10.1093/ilar/ilx004.
  • Zhang, K, Demner-Fushman D. Automated classification of eligibility criteria in clinical trials to facilitate patient-trial matching for specific patient populations. J Am Med Inform Assoc. 2017 Jul 1;24(4):781-787. doi: 10.1093/jamia/ocw176.
  • 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

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