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  • Antani SK. Tuberculosis Chest X-ray Image Data Sets
  • Jaeger S, Antani S, Thoma GR. Tuberculosis Screening of Chest Radiographs. 2 June 2011, SPIE Newsroom. DOI: 10.1117/2.1201105.003732i.
  • Jaeger S, Candemir S, Antani SK, Wang Y, Lu P, Thoma GR. Two public chest X-ray datasets for computer-aided screening of pulmonary diseases. Quant Imaging Med Surg. 2014 Dec;4(6):475-7. doi: 10.3978/j.issn.2223-4292.2014.11.20.
  • Datta S, Si Y, Rodriguez L, Shooshan S, Demner-Fushman D, roberts K. Understanding Spatial Language in Radiology: Representation Framework, Annotation, and Spatial Relation Extraction from Chest X-ray Reports using Deep Learning. arXiv preprint arXiv:1908.04485, 2019.
  • Rajaraman S, Silamut K, Hossain MA, Ersoy I, Maude RJ, Jaeger S, Thoma GR, Antani SK. Understanding the learned behavior of customized convolutional neural networks toward malaria parasite detection in thin blood smear images. J Med Imaging (Bellingham). 2018 Jul;5(3):034501. doi: 10.1117/1.JMI.5.3.034501. Epub 2018 Jul 18.
  • Zou J, Antani SK, Thoma G. Unified Deep Neural Network for Segmentation and Labeling of Multi-Panel Biomedical Figures Journal of the Association for Information Science and Technology (JASIST), 2019
  • Zou J. Unified Deep Neural Network for Segmentation and Labeling of Multi-Panel Biomedical Figures Journal of the Association for Information Science and Technology (JASIST), 2019
  • Mundkur ML, Callaghan FM, Abhyankar S, McDonald CJ. Use of Electronic Health Record Data to Evaluate the Impact of Race on 30-Day Mortality in Patients Admitted to the Intensive Care Unit. J Racial Ethn Health Disparities. 2017 Aug;4(4):539-548. doi: 10.1007/s40615-016-0256-6. Epub 2016 Jun 20.
  • Zhang Y, Baik SH, Newhouse JP. Use of intelligent assignment to Medicare Part D plans for people with schizophrenia could produce substantial savings. Health Aff (Millwood). 2015 Mar;34(3):455-60. doi: 10.1377/hlthaff.2014.1227.
  • Long LR, Thoma GR. Use of Shape Models to Search Digitized Spine X-Rays IEEE Computer-Based Medical Systems. 2000 June;: 255-60.
  • 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.
  • Xue Z, Antani SK, Long LR, Thoma GR. Using deep learning for detecting gender in adult chest radiographs. SPIE Medical Imaging 2018
  • Xu X, Lee DJ, Antani SK, Long LR, Archiband JK. Using Relevance Feedback with Short-term Memory for Content-based Spine X-ray Image Retrieval. J Neurocomputing. June 2009;72(10-12):2259-69.
  • Rondonotti E, Koulaouzidis A, Karargyris A, Giannakou A, Fini L, Soncini M, Pennazio M, Douglas S, Shams A, Lachlan N, Zahid A, Mandelli G, Girelli C. Utility of 3-dimensional image reconstruction in the diagnosis of small-bowel masses in capsule endoscopy (with video). Gastrointest Endosc. 2014 Oct;80(4):642-51. doi: 10.1016/j.gie.2014.04.057. Epub 2014 Jul 3.
  • Mundkur ML, McDonald CJ. Utilizing Medicare claims for the assessment of influenza vaccination coverage in the US elderly. J Gen Intern Med, 2016. 31: p. S463.
  • Antani S, Long LR, Thoma GR, Stanley RJ. Vertebra Shape Classification using MLP for Content-Based Image Retrieval International Neural Networks Society and IEEE Neural Networks Society. 2003 July 2003;:160-65.
  • Ducut E, Liu F, Avila JM, Encinas MA, Diwa M, Fontelo P. Virtual Microscopy in a Developing Country: A Collaborative Approach to Building an Image Library. Journal of eHealth Technology and Application. 2010 Sep;8(2):112-5.
  • Fontelo P, DiNino E, Johansen K, Khan A, Ackerman MJ. Virtual Microscopy: Potential Applications in Medical Education and Telemedicine in Countries with Developing Economies. Proceedings of the 38th Hawaii International Conference on System Sciences; 2005 Jan 3-6; Big Island, Hawaii: 7 pages. IEEE Computer Society.
  • Ratiu P, Hillen B, Glaser J, Jenkins DB. Visible Human 2.0 - The Next Generation. In: Westwood JD, Hoffman HM, Mogel GT, Phillips R, Robb RA, Stredney D, editors. Stud Health Technol Inform [Studies in Health Technology and Informatics] -- Proceedings of the 11th annual Medicine Meets Virtual Reality conference; 2003 Jan;94:275-81. Amsterdam: IOS Press.
  • Ackerman MJ. Visible Human Project. McGraw-Hill 2004 Yearbook of Science & Technology. New York: McGraw-Hill. 2004. p. 369-72.
  • Ackerman MJ. Visible Human Project: From Data to Knowledge. In: Haux R, Kulikowski C, editors. Yearbook of Medical Informatics 2002: Medical Imaging Informatics. International Medical Informatics Association (IMIA). p. 115-7.
  • Jeronimo J, Massad LS, Schiffman M for the NIH-ASCCP Research Group. Visual Appearance of the Uterine Cervix: Correlation with Human Papillomavirus Detection and Type Am J Obstet Gynecol. 2007 Jul;197(1):47.e1-8
  • Kim I, Rajaraman S, Antani SK. Visual Interpretation of Convolutional Neural Network Predictions in Classifying Medical Image Modalities. Diagnostics (Basel). 2019 Apr 3;9(2). pii: E38. doi: 10.3390/diagnostics9020038.
  • Rajaraman S, Candemir S, Kim I, Thoma GR, Antani SK. Visualization and Interpretation of Convolutional Neural Network Predictions in Detecting Pneumonia in Pediatric Chest Radiographs. Appl. Sci. 2018, 8, 1715.
  • Moorhead R, Johnson C, Munzner T, Pfister H, Rheingans P, Yoo TS. Visualization Corner: Visualization Research Challenges: A Report Summary. IEEE Computing in Science and Engineering. 2006 Jul-Aug;8(4):66-73. DOI: 10.1109/MCSE.2006.77.

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