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  • Rajaraman S, Antani SK. Visualizing Salient Network Activations in Convolutional Neural Networks for Medical Image Modality Classification. Santosh K., Hegadi R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1036. Springer, Singapore
  • 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.
  • Ben Abacha A, Demner-Fushman D. On the Summarization of Consumer Health Questions. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy 2019.
  • Allam A, Magy M, Thoma G, Krauthammer M. Neural networks versus Logistic regression for 30 days all-cause readmission prediction. Sci Rep. 2019 Jun 26;9(1):9277. doi: 10.1038/s41598-019-45685-z.
  • Rajaraman S, Jaeger S, Antani SK. Performance evaluation of deep neural ensembles toward malaria parasite detection in thin-blood smear images. PeerJ 7:e6977
  • Ben Abacha A, Demner-Fushman D. On the Role of Question Summarization and Information Source Restriction in Consumer Health Question Answering. AMIA Informatics Summit, March 2019.
  • Chowdhuri S, McCrea S, Demner-Fushman D, Overby TC. Extracting Biomedical Terms from Postpartum Depression Online Health Communities. AMIA Jt Summits Transl Sci Proc. 2019 May 6;2019:592-601.
  • Zhang XA, Yates A, Vasilevsky N, Gourdine JP, Callahan TJ, Carmody LC, Danis D, Joachimiak MP, Ravanmehr V, Pfaff ER, Champion J, Robasky K, Xu H, Fecho K, Walton NA, Zhu RL, Ramsdill J, Mungall CJ, Kohler S, Haendel MA, McDonald CJ, Vreeman DJ, Peden DB, Bennett TD, Feinstein JA, Martin B, Stefanski AL, Hunter LE, Chute CG, Robinson PN. Semantic integration of clinical laboratory tests from electronic health records for deep phenotyping and biomarker discovery. NPJ Digit Med. 2019;2. pii: 32. doi: 10.1038/s41746-019-0110-4. Epub 2019 May 2.
  • Kesav N, Yang Q, Losert W, Kim J, Jaeger S, Sen HN. Novel automated processing techniques of fluorescein angiography (FA) images in patients with Uveitis. Annual Meeting of the Association for Research in Vision and Ophthalmology (ARVO).
  • Ionescu B, Muller H, Peteri R, Dang-Nguyen DT, Piras L, Riegler M, Tran MT, Lux M, Gurrin C, Cid YD, Liauchuk V, Kovalev V, Ben Abacha A, Hasan SA, Datla V, Liu J, Demner-Fushman D, Pelka O, Friedrich CM, Chamberlain J, Clark C, de Herrera AGS, Garcia N, Kavallieratou E, del Blanco CR, Rodriguez CC, Vasillopoulos N, Karampidis K. Multimedia retrieval in medicine, lifelogging, security and nature. International Conference of the Cross-Language Evaluation Forum for European Languages, Springer, Cham, 358-386, 2019
  • Kim I, Rajaraman S, Antani SK. Visual Interpretation of Convolutional Neural Network Predictions in Classifying Medical Image Modalities. Diagnostics, 9(2), 38, 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.
  • Guo P, Singh S, Xue Z, Long LR, Antani SK. Deep Learning for Assessing Image Focus for Automated Cervical Cancer Screening. 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI) DOI: 10.1109/BHI.2019.8834495.
  • Ben Abacha A, Demner-Fushman D. On the Role of Question Summarization and Information Source Restriction in Consumer Health Question Answering. Proceedings of the AMIA 2019 Informatics Summit, San Francisco, CA, USA, March 25-28, 2019.
  • 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.
  • Goodwin T, Harabagiu S. The Impact of Inferring Treatments on Information Retrieval for Precision Medicine. Proceedings of the AMIA 2019 Informatics Summit, San Francisco, CA, USA, March 25-28, 2019.
  • Zolnoori M, Fung K, Patrick DB, Fontelo P, Kharrazi H, Faiola A, Shah ND, Shirley WYS, Eldredge CE, Luo J, Conway M, Zhu J, Park SK, Xu K, Moayyed H. The PsyTAR dataset: From patients generated narratives to a corpus of adverse drug events and effectiveness of psychiatric medications. Data Brief. 2019 Mar 15;24:103838. doi: 10.1016/j.dib.2019.103838. eCollection 2019 Jun.
  • 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.
  • Rodriguez L, Demner-Fushman D. Finding Understudied Disorders Potentially Associated withMaternal Morbidity and Mortality AMIA Informatics Summit, March 2019.
  • Kilicoglu H, Peng Z, Tafreshi S, Tran T, Rosemblat G, Schneider J. Confirm or Refute?: A Comparative Study on Citation Sentiment Classification in Clinical Research Publications. J Biomed Inform. 2019 Feb 9:103123. doi: 10.1016/j.jbi.2019.103123.
  • Demner-Fushman D. Clinical, Consumer Health, and Visual Question Answering. Springer Nature Switzerland AG 2019. J. A. Lossio-Ventura et al. (Eds.): SIMBig 2018, CCIS 898, pp. 1–6, 2019.
  • 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.
  • Rodriguez L, Demner-Fushman D. Finding Understudied Disorders Potentially Associated with Maternal Morbidity and Mortality. AJP Rep. 2019 Jan;9(1):e36-e43. doi: 10.1055/s-0039-1683363. Epub 2019 Mar 4.
  • Zolnoori M, Fung K, Patrick TB, Fontelo P, Kharrazi H, Faiola A, Wu YSS, Eldredge CE, Luo J, Conway M, Zhu J, Park SK, Xu K, Moayyed H, Goudarzvand S. A systematic approach for developing a corpus of patient reported adverse drug events: A case study for SSRI and SNRI medications. NCBINCBI Logo Skip to main content Skip to navigation Resources How To About NCBI Accesskeys PubMed US National Library of Medicine National Institutes of Health Search databaseSearch term 30611893[uid] Clear inputSearch Create RSSCreate alertAdvancedHelp Result Filters Format: AbstractSend to J Biomed Inform. 2019 Feb;90:103091. doi: 10.1016/j.jbi.2018.12.005. Epub 2019 Jan 4.

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