• Ionescu B, Müller H, Péteri R, Dang-Nguyen DT, Zhou L, Piras L, Riegler M, Halvorsen P, Tran MT, Lux M, Gurrin C, Chamberlain J, Clark A, Campello A, de Herrera AGS, Ben Abacha A, Datla VV, Hasan SA, Liu J, Demner-Fushman D, Pelka O, Friedrich CM, Cid YD, Kozlovski S, Liauchuk V, Kovalev V, Berari P, Brie P, Fichou D, Dogariu M, Stefan L, Constantin M. ImageCLEF 2020: Multimedia Retrieval in Lifelogging, Medical, Nature, and Internet Applications. ImageCLEF 2020: Multimedia Retrieval in Lifelogging, Medical, Nature, and Internet Applications. ECIR (2) 2020: 533-541.

  Abstract | URL:  https://link.springer.com/chapter/10.1007/978-3-030-45442-5_69

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• Sornapudi S, Brown G, Xue Z, Long LR, Allen L, Antani SK. Comparing Deep Learning Models for Multi-cell Classification in Liquid- based Cervical Cytology Image. AMIA Annu Symp Proc. 2019; 2019: 820–827.

  Abstract | PMID:  32308878 | PMCID:  PMC7153123

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• Zou J, Xue Z, Brown G, Long LR, Antani SK. Deep learning for nuclei segmentation and cell classification in cervical liquid based cytology. Proc. SPIE 11318, Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications, 1131811 (2 March 2020); doi: 10.1117/12.2549547

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• Yang F, Quizon N, Silamut K, Maude RJ, Jaeger S, Antani SK. Cascading YOLO: Automated Malaria Parasite Detection for Plasmodium Vivax in Thin Blood Smears. To be presented at SPIE Medical Imaging, Feb.18-20, 2020, Houston, USA.

  Abstract | Final Paper_SPIE_Feng Yang_Final.pdf

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• Ben Abacha A, Hasan SA, Datls W, Liu J, Demner-Fushman D, Muller H. VQA-Med: Overview of the medical visual question answering task at imageclef 2019. CEUR Workshop Proceedings, 9-12, 2019.

  Abstract | pub9992.pdf

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• Rae A, Savery M, Mork JG, Demner-Fushman D. A High Recall Classifier for Selecting Articles for MEDLINE Indexing. AMIA Fall Symposium, 2019.

  Abstract | pub9984.pdf

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• Yang F, Yu H, Silamut K, Maude RJ, Jaeger S, Antani SK. Parasite Detection in Thick Blood Smears Based on Customized Faster-RCNN. Proceedings of AIPR2019, Washington DC, USA, Oct 15-17, 2019.

  Abstract | pub10004.pdf

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• Yang F, Yu H, Silamut K, Maude R, Jaeger S, Antani SK. Smartphone-Supported Malaria Diagnosis Based on Deep Learning. Proceedings of 10th Workshop on Machine Learning in Medical Imaging (MLMI 2019) in conjunction with MICCAI, Shenzhen, China, Oct 13-17, 2019.

  Abstract | URL:  https://link.springer.com/chapter/10.1007/978-3-030-32692-0_9

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• 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

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• 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

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• Ben Abacha A, Mrabet Y, Sharp M, Goodwin T, Shooshan S, Demner-Fushman D. Bridging the Gap Between Consumers’ Medication Questions and Trusted Answers. Stud Health Technol Inform. 2019 Aug 21;264:25-29. doi: 10.3233/SHTI190176.

  Abstract | pub9965.pdf

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• Ben Abacha A, Shivade C, Demner-Fushman D. Overview of the MEDIQA 2019 Shared Task on Textual Inference, Question Entailment and Question Answering. Proceedings of the 18th BioNLP Workshop and Shared Task, Florence, Italy, August 1, 2019.

  Abstract | pub9964.pdf

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• Ben Abacha A, Shivade C, Demner-Fushman D. Overview of the MEDIQA 2019 Shared Task on Textual Inference, Question Entailment and Question Answering. Proceedings of the BioNLP 2019 workshop.

  Abstract | URL:  https://www.aclweb.org/anthology/W19-5039.pdf

  AbstractExternal link
• Demner-Fushman D, Cohen KB, Ananiadou S, Tsujii J. Sesame Street at BioNLP 2019. Proceedings of the BioNLP 2019 workshop.

  Abstract | URL:  https://www.aclweb.org/anthology/W19-5000.pdf

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• 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.

  Abstract | pub9938.pdf

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• 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.

  Abstract | pub9936.pdf

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• 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.

  Abstract | pub9937.pdf

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• 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.

  Abstract | pub9929.pdf

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• 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.

  Abstract | pub9963.pdf

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• 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.

  Abstract | PMID:  30987172 | URL:  https://www.mdpi.com/2075-4418/9/2/38/htm

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• 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.

  Abstract | pub9967.pdf

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• 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.

  Abstract | pub9923.pdf

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• 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.

  Abstract | pub9901.pdf

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• 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.

  Abstract | pub9899.pdf

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• 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.

  Abstract | PMID:  30730032

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