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  • Rosemblat G, Fiszman, M, Shin D, Kilicoglu H. Towards a characterization of apparent contradictions in the biomedical literature using context analysis. Journal of Biomedical Informatics. 2019. In Press. https://doi.org/10.1016/j.jbi.2019.103275.
  • Rajaraman S, Candemir S, Xue Z, Alderson P, Thoma G, Antani SK. A Novel Stacked Model Ensemble for Improved TB Detection in Chest Radiographs. In Santosh KC et al. (Eds.). Medical Imaging: Artificial Intelligence, Image Recognition, and Machine Learning Techniques. (pp. 1-26). New York, NY: CRC Press, Taylor & Francis Group.
  • Divita G, Rosemblat G, Browne AC. Building a medical Spanish lexicon. AMIA Annu Symp Proc. 2007 Oct 11:941.
  • 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 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.
  • 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, Antani SK. A review on lung boundary detection in chest X-rays. Int J Comput Assist Radiol Surg. 2019 Feb 7. doi: 10.1007/s11548-019-01917-1.
  • Ben Abacha A, Demner-Fushman D. On the role of question summarization and information source restriction in consumer health question answering. In Proceedings of the AMIA 2019 Informatics Summit, San Francisco, CA, USA, 2019.
  • Hu L, Bell D, Antani SK, Xue Z, Yu K, Horning MP, Gachuhi N, Wilson B, Jaiswal MS, Befano B, Long LR, Herrero R, Einstein MH, Burk RD, Demarco M, Gage JC, Wentzensen N, Schiffman M. An Observational Study of Deep Learning and Automated Evaluation of Cervical Images for Cancer Screening. J Natl Cancer Inst. 2019 Jan 10. doi: 10.1093/jnci/djy225
  • Jaeger S, Juarez-Espinosa OH, Candemir S, Poostchi M, Yang F, Kim L, Ding M, Folio LR, Antani SK, Gabrielian A, Hurt D, Rosenthal A, Thoma G. Detecting drug-resistant tuberculosis in chest radiographs. Int J Comput Assist Radiol Surg. 2018 Dec;13(12):1915-1925. doi: 10.1007/s11548-018-1857-9. Epub 2018 Oct 3.
  • Lu C, Demner-Fushman D. Improving Spelling Correction with Consumer Health Terminology Improving Spelling Correction with Consumer Health Terminology AMIA 2018 Annual Symposium, San Francisco, CA, November 3-7, 2018, p. 2053.
  • 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.
  • Dhoot R, Humphrey JM, O'Meara P, Gardner A, McDonald CJ, Ogot K, Antani SK, Abuya J, Kohli M. Implementing a mobile diagnostic unit to increase access to imaging and laboratory services in western Kenya. BMJ Glob Health. 2018 Oct 8;3(5):e000947. doi: 10.1136/bmjgh-2018-000947. eCollection 2018.
  • Poostchi M, Ilker E, McMenamin K, Gordon E, Palaniappan N, Pierce S, Maude RJ, Bansal A, Srinivasan P, Miller L, Palaniappan K, Thoma GR, Jaeger S. Malaria parasite detection and cell counting for human and mouse using thin blood smear microscopy. J Med Imaging (Bellingham). 2018 Oct;5(4):044506. doi: 10.1117/1.JMI.5.4.044506. Epub 2018 Dec 12.
  • 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).
  • Vajda S, Karargyris A, Jaeger S, Santosh KC, Candemir S, Xue Z, Antani SK, Thoma GR. Feature Selection for Automatic Tuberculosis Screening in Frontal Chest Radiographs. J Med Syst. 2018 Jun 29;42(8):146. doi: 10.1007/s10916-018-0991-9.
  • 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.
  • 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.
  • Thamizhvani TR, Lakshmanan S, Rajaraman S. Mobile application-based computer-aided diagnosis of skin tumours from dermal images. The Imaging Science Journal, 66:6, 382-391, 2018, DOI: 10.1080/13682199.2018.1492682

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