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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.
  • 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.
  • 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.
  • 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.
  • 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
  • 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.
  • 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.
  • 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.
  • Rajaraman S, Jaeger S, Antani SK. Performance evaluation of deep neural ensembles toward malaria parasite detection in thin-blood smear images. PeerJ 7:e6977
  • 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.
  • 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.
  • 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.
  • 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.
  • Zolnoori M, Fung K, Fontelo P, Kharrazi H, Faiola A, Wu YSS, Stoffel V, Patrick T. Identifying the Underlying Factors Associated With Patients' Attitudes Toward Antidepressants: Qualitative and Quantitative Analysis of Patient Drug Reviews. JMIR Ment Health. 2018 Sep 30;5(4):e10726. doi: 10.2196/10726.
  • Fontelo P, Liu F. A review of recent publication trends from top publishing countries. Syst Rev. 2018 Sep 27;7(1):147. doi: 10.1186/s13643-018-0819-1.
  • Rajaraman S, Candemir S, Kim I, Thoma GR, Antani SK. Visualization and Interpretation of Convolutional Neural Network Predictions in Detecting Pneumonia in Pediatric Chest Radiographs. Appl. Sci. 2018, 8, 1715.
  • Sylim P, Liu F, Marcelo A, Fontelo P. Blockchain Technology for Detecting Falsified and Substandard Drugs in Distribution: Pharmaceutical Supply Chain Intervention. JMIR Res Protoc. 2018 Sep 13;7(9):e10163. doi: 10.2196/10163.
  • 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.
  • Jaeger S, Juarez-Espinosa O, Candemir S, Poostchi Mohammadabadi M, Yang F, Kim L, Ding M, Folio L, Antani SK, Gabrielian A, Hurt D, Rosenthal A, Thoma GR. Detecting drug-resistant tuberculosis in chest radiographs International Journal of Computer Assisted Radiology and Surgery https://doi.org/10.1007/s11548-018-1857-9
  • Beare R, Lowekamp B, Yaniv Z. Image Segmentation, Registration and Characterization in R with SimpleITK. J Stat Softw. 2018 Aug;86. pii: 8. doi: 10.18637/jss.v086.i08. Epub 2018 Sep 4.
  • McDonald CJ, Maglott D, Abhyankar S, Goodwin RM, Kanduru A, Lu S, Lynch P, Vreeman D, Wang Y, Wood G. US Realm, Chapter 14, Use Case – Clinical Genomics Code Systems. in HL7 Version 2.5.1 Implementation Guide: Lab Results Interface (LRI), DTSU3. HL7 International (Ann Arbor).
  • McDonald CJ, Maglott D, Abhyankar S, Goodwin RM, Kanduru A, Lu S, Lynch P, Vreeman D, Wang Y, Wood G. US Realm, Chapter 5, Use Case – Clinical Genomics Results Reporting in HL7 Version 2.5.1 Implementation Guide: Lab Results Interface (LRI), DTSU3. HL7 International (Ann Arbor).

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