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  • 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
  • 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.
  • 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.
  • Guo P, Xue Z, Long LR, Antani SK. Cross-Dataset Evaluation of Deep Learning Networks for Uterine Cervix Segmentation. Diagnostics (Basel). 2020 Jan 14;10(1). pii: E44. doi: 10.3390/diagnostics10010044.
  • 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.
  • Cheng P, Lu P, Wang P, Zhou W, Yu W, Jaeger S, Li J, Wu T, Ke X, Zheng B, Antani SK, Candemir S, Quan S, Lure F, Li H, Guo L. Applying Deep Learning and Radiomics to Determine Biological Lung and Heart Age from Chest Radiographs. Chinese Congress of Radiology.
  • Wang X, Guan Y, Lu P, Cheng G, Zhou W, Jaeger S, Zhen B, Antani SK, Yin X, Yu W, Guo L, Quan S, Lure F, Hurt D, Gabrielian A, Li H, Ke X. Screening of Tuberculosis in a TB High-burden Large Rural Region in China with Deep Learning Multi-modality Artificial Intelligence. Chinese Congress of Radiology.
  • 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.
  • Rajaraman S, Jaeger S, Antani SK. Performance evaluation of deep neural ensembles toward malaria parasite detection in thin-blood smear images. PeerJ. doi: 10.7717/peerj.6977.
  • 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.
  • Goodwin T, Demner-Fushman D. Bridging the Knowledge Gap: Enhancing Question Answering with World and Domain Knowledge. arXiv preprint arXiv:1910.07429
  • 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.
  • Yang F, Poostchi M, Yu H, Zhou Z, Silamut K, Yu J, Maude RJ, Jaeger S, Antani SK. Deep Learning for Smartphone-Based Malaria Parasite Detection in Thick Blood Smears. IEEE J Biomed Health Inform. 2019 Sep 23. doi: 10.1109/JBHI.2019.2939121.
  • Kho SU, Sheth A, Bodenreider O. Automatic Identification of Individual Drugs in Death Certificates. Stud Health Technol Inform. 2019 Aug 21;264:183-187. doi: 10.3233/SHTI190208.
  • Vasilakes J, Fan Y, Rizvi R, Bompelli A, Bodenreider O, Zhang R. Normalizing Dietary Supplement Product Names Using the RxNorm Model. Stud Health Technol Inform. 2019 Aug 21;264:408-412. doi: 10.3233/SHTI190253.
  • 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.
  • Datta S, Si Y, Rodriguez L, Shooshan S, 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. arXiv preprint arXiv:1908.04485, 2019.
  • Xue Y, Zhou Q, Ye J, Long LR, Antani SK, Cornwell C, Xue Z, Huang X. Synthetic Augmentation and Feature-based Filtering for Improved Cervical Histopathology Image Classification. ArXiv, abs/1907.10655.
  • 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.
  • 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.
  • 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
  • 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 (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.
  • 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.
  • 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.
  • 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.
  • 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
  • Scarton LA, Wang L, Kilicoglu H, Jahries M, Del Fiol M. Expanding vocabularies for complementary and alternative medicine therapies. Int J Med Inform. 2019 Jan;121:64-74. doi: 10.1016/j.ijmedinf.2018.11.009. Epub 2018 Nov 22.
  • Rindflesch TC, Blake CL, Cairelli MJ, Fiszman M, Zeiss CJ, Kilicoglu H. Investigating the role of interleukin-1 beta and glutamate in inflammatory bowel disease and epilepsy using discovery browsing. J Biomed Semantics. 2018 Dec 27;9(1):25. doi: 10.1186/s13326-018-0192-y.

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