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  • 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.
  • Almubarak H, Guo P, Stanley RJ, Long LR, Antani SK, Thoma GR. Algorithm Enhancements for Improvement of Localized Classification of Uterine Cervical Cancer Digital Histology Images. in Handbook of Research on Emerging Perspectives on Healthcare Information Systems and Informatics,. IGI Global (Hershey, PA).
  • Tang P, McDonald CJ. Computer-Based Patient-Record Systems - Chapter 9. In Shortliffe E, Perreault L, eds. Medical Informatics. New York: springer. 2001:327-358. DOI: 10.1007/978-0-387-21721-5_9.
  • 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.
  • 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
  • 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.
  • 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
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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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