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  • 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.
  • 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.
  • 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
  • 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.
  • Zeiss CJ, Donwook S, Vander Wyk B, Beck AP, Zatz N, Sneiderman CA, Kilicoglu H. Menagerie: A text-mining tool to support animal-human translation in neurodegeneration research. PLoS One. 2019 Dec 17;14(12):e0226176. doi: 10.1371/journal.pone.0226176. eCollection 2019.
  • Mrabet Y, Demner-Fushman D. On Agreements in Visual Understanding. 2019 Conference on Neural Information Processing Systems. 2019 Conference on Neural Information Processing Systems, December 8-14, 2019. Vancouver, Canada.
  • Yu H, Yang F, Silamut R, Maude S, Jaeger S, Antani SK. Automatic Blood Smear Analysis with Artificial Intelligence and Smartphones. ASTMH 68th Annual Meeting, Washington DC, Nov. 20-24, 2019.
  • Mao Y, Fung K, Demner-Fushman D. Drug-drug Interaction Extraction via Transfer Learning. AMIA Fall Symposium, 2019.
  • Lure F, Jaeger S, Cheng G, Li H, Lu P, Yu W, Kung J, Guan Y. Applying Multi-modality Artificial Intelligence for Screening of Tuberculosis in a TB High-burden Large Rural Region in China TBScience, 50th Union World Conference on Lung Health, Hyderabad, India.
  • Yang F, Poostchi M, Silamut K, Maude RJ, Jaeger S, Thoma G. Automated Parasite Classification of Malaria on Thick Blood Smears. ASTMH 67th Annual Meeting, New Orleans, LA, Oct. 28 – Nov. 1, 2018.
  • 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.
  • 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.
  • Yang F, Yu H, Silamut K, Maude RJ, Jaeger S, Antani SK. Smartphone-Supported Malaria Diagnosis Based on Deep Learning. In: Suk HI., Liu M., Yan P., Lian C. (eds) Machine Learning in Medical Imaging. MLMI 2019. Lecture Notes in Computer Science, vol 11861. Springer, Cham.
  • 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
  • Demner-Fushman D, Mrabet Y, Ben Abacha A. Consumer health information and question answering: helping consumers find answers to their health-related information needs. JAMIA, 2019.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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 (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.
  • 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.
  • 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.
  • 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.
  • 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 GR. 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.
  • 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.
  • 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).
  • Yang F, Yu H, Poostchi M, Silamut K, Maude RJ, Jaeger S. Smartphone-Supported Automated Malaria Parasite Detection. SIIM conference on Machine Intelligence in Medical Imaging, 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
  • Xue Z, Rajaraman S, Long LR, Antani SK, Thoma GR. Gender Detection from Spine X-ray Images Using Deep Learning. Proc. IEEE International Symposium on Computer-Based Medical Systems (CBMS), Karlstad, Sweden, 2018. pp. 54-58, DOI:10.1109/CBMS.2018.00017.
  • Kim J, Candemir S, Chew E, Thoma GR. Region of Interest Detection in Fundus Images Using Deep Learning and Blood Vessel Information. The 31th IEEE International Symposium on Computer-Based Medical Systems. (IEEE CBMS 2018), pp. 357-362, Karlstad, Sweden, June 2018.
  • Sornapudi S, Stanley RJ, Stoecker WV, Almubarak H, Long LR, Antani SK, Thoma GR, Zuna R, Frazier SR. Deep Learning Nuclei Detection in Digitized Histology Images by Superpixels. J Pathol Inform. 2018 Mar 5;9:5. doi: 10.4103/jpi.jpi_74_17. eCollection 2018.
  • Santosh KC, Antani SK. Automated chest x-ray screening: Can lung region symmetry help detect pulmonary abnormalities? doi: 10.1109/TMI.2017.2775636 vol. 37, no. 5, 1168-1177.
  • Rajaraman S, Antani SK, Poostchi Mohammadabadi M, Silamut K, Hossain MA, Maude RJ, Jaeger S, Thoma GR. Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images. PeerJ. 2018 Apr 16;6:e4568. doi: 10.7717/peerj.4568. eCollection 2018.
  • Moallem G, Sari-Sarraf H, Poostchi M, Maude RJ, Silamut K, Hossain MA, Antani SK, Jaeger S, Thoma G. Detecting and segmenting overlapping red blood cells in microscopic images of thin blood smears. Proc. SPIE 10581, Medical Imaging 2018:Digital Pathology, 105811F (6 March 2018); doi: 10.1117/12.2293762.

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