• Datta S, Rodriguez L, Shooshan SE, 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. Journal of Biomedical Informatics, 103473.

  Abstract | URL:  https://arxiv.org/pdf/1908.04485.pdf

  AbstractExternal link
• Goodwin T, Demner-Fushman D. A customizable deep learning model for nosocomial risk prediction from critical care notes with indirect supervision. Journal of the American Medical Informatics Association, 2020: 27 (4), 567-576.

  Abstract | PMID:  32065628 | PMCID:  PMC7075529

  Abstract
• Voorhees EM, Alam T, Bedrick S, Demner-Fushman D, Hersh WR, Lo K, Roberts K, Soboroff I, Wang LL. TREC-COVID: Constructing a Pandemic Information Retrieval Test Collection. CoRR abs/2005.04474 (2020)

  Abstract | URL:  https://arxiv.org/abs/2005.04474

  AbstractExternal link
• Rajaraman S, Sornapudi S, Alderson PO, Folio LR, Antani SK. Interpreting Deep Ensemble Learning through Radiologist Annotations for COVID-19 Detection in Chest Radiographs. medRxiv 2020.07.15.20154385; doi: https://doi.org/10.1101/2020.07.15.20154385.

  Abstract | pub10047.pdf

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• Rajaraman S, Siegelman J, Alderson PO, Folio LS, Folio LR, Antani SK. Iteratively Pruned Deep Learning Ensembles for COVID-19 Detection in Chest X-Rays. IEEE Access, vol. 8, pp. 115041-115050, 2020, doi: 10.1109/ACCESS.2020.3003810

  Abstract | pub10046.pdf

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• Zheng Q, Lu Y, Lure F, Jaeger S, Lu P. Clinical and radiological features of novel coronavirus pneumonia. Journal of X-Ray Science and Technology, vol. 28, no. 3, pp. 391-404, 2020.

  Abstract | pub10048.pdf

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• Roberts K, Alam T, Bedrick S, Demner-Fushman D, Lo K, Soboroff I, Voorhees E, Wang LL, Hersh WR. TREC-COVID: Rationale and Structure of an Information Retrieval Shared Task for COVID-19. Journal of the American Medical Informatics Association, 2020.

  Abstract | URL:  https://academic.oup.com/jamia/article/doi/10.1093/jamia/ocaa091/5828938

  AbstractExternal link
• Guo P, Xue Z, Mtema Z, Yeates K, Ginsburg O, Demarco M, Long LR, Schiffman M, Antani SK. 2. Ensemble Deep Learning for Cervix Image Selection toward Improving Reliability in Automated Cervical Precancer Screening. Diagnostics (Basel) 2020 Jul 3;10(7):451.

  Abstract | PMID:  32635269 | PMCID:  PMC7400120

  Abstract
• Alzamzmi GA, Hsu L, Li W, Sachdev V, Antani SK. Echo Doppler Flow Classification and Goodness Assessment with Convolutional Neural Networks. 2019 18th IEEE International Conference On Machine Learning And Applications (ICMLA), Boca Raton, FL, USA, 2019, pp. 1744-1749, doi: 10.1109/ICMLA.2019.00283

  Abstract | pub10044.pdf

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• Alzamzmi GA, Hsu L, Li W, Sachdev V, Antani SK. Fully automated spectral envelope and peak velocity detection from Doppler echocardiography images. Proc. SPIE 11314, Medical Imaging 2020: Computer-Aided Diagnosis, 113144G (16 March 2020); https://doi.org/10.1117/12.2551183

  Abstract

  Abstract
• Alzamzmi GA, Hsu L, Li W, Sachdev V, Antani SK. Harnessing Machine Intelligence in Automatic Echocardiogram Analysis: Current Status, Limitations, and Future Directions. IEEE Reviews in Biomedical Engineering, doi: 10.1109/RBME.2020.2988295

  Abstract | pub10042.pdf

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• Salekin S, Alzamzmi GA, Paul R, Goldgof D, Kasturi R, Ho T, Sun Y. Harnessing the Power of Deep Learning Methods in Healthcare: Neonatal Pain Assessment from Crying Sound.

  Abstract | pub10045.pdf

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• Jain SK, Andronikou S, Goussard P, Antani SK, Gomez-Pastrana D, Delacour C, Starke JR, Ordonez AA, Jean-Philippe P, Browning RS, Perez-Velez C. Advanced imaging tools for childhood tuberculosis: potential applications and research needs. . The Lancet Infectious Diseases. DOI:https://doi.org/10.1016/S1473-3099(20)30177-8

  Abstract | pub10041.pdf

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• Alzamzmi GA, Rajaraman S, Antani SK. Accelerating Super-Resolution and Visual Task Analysis in Medical Images. Appl. Sci. 2020, 10, 4282.

  Abstract | pub10040.pdf

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• Alzamzmi GA, Rajaraman S, Antani SK. Unified Representation Learning for Efficient Medical Image Analysis 2020, [Online]

  Abstract | pub10039.pdf | URL:  https://arxiv.org/abs/2006.11223

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• Rajaraman S, Antani SK. Weakly Labeled Data Augmentation for Deep Learning: A Study on COVID-19 Detection in Chest X-Rays. Diagnostics 2020, 10, 358.

  Abstract | pub10038.pdf

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• Xue Z, Novetsky A, Einstein M, Marcus J, Befano B, Guo P, Demarco M, Wenzenten N, Long LR, Schiffman M, Antani SK. A demonstration of automated visual evaluation of cervical images taken with a smartphone camera. Int J Cancer . 2020 Apr 30

  Abstract | PMID:  32356305

  Abstract
• Rajaraman S, Siegelman J, Alderson PO, Folio LS, Folio LR, Antani SK. Iteratively Pruned Deep Learning Ensembles for COVID-19 Detection in Chest X-rays. 2020, [Online].

  Abstract | URL:  https://arxiv.org/abs/2004.08379

  AbstractExternal link
• 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

  AbstractExternal link
• Rajaraman S, Kim I, Antani SK. Detection and visualization of abnormality in chest radiographs using modality-specific convolutional neural network ensembles. PeerJ 8:e8693 https://doi.org/10.7717/peerj.8693

  Abstract | pub10034.pdf

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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

  Abstract
• Guo P, Xue Z, Long LR, Antani SK. 1. Anatomical landmark segmentation in uterine cervix images using deep learning. Proc. SPIE 11318, Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications, 1131810 (2 March 2020)

  Abstract | pub10061.pdf

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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

  Abstract

  Abstract
• 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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• Rajaraman S, Antani SK. Modality-Specific Deep Learning Model Ensembles Toward Improving TB Detection in Chest Radiographs. IEEE Access, vol. 8, pp. 27318-27326, 2020.

  Abstract | pub10033.pdf

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