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  • 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.
  • Moallem G, Sari-Sarraf H, Poostchi Mohammadabadi M, Maude R, Silamut K, Antani SK, Jaeger S. Detecting and segmenting overlapping red blood cells in microscopic images of thin blood smears. SPIE Medical Imaging, 2018.
  • 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).
  • Jaeger S, Antani SK, Rajaraman S, Yang F, Yu H. Malaria Screening: Research into Image Analysis and Deep Learning. Report to the Board of Scientific Counselors September 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).
  • Rae A, Kim J, Le DX, Thoma GR. Main Content Detection in HTML Journal Articles. DocEng ’18: ACM Symposium on Document Engineering 2018, August 28–31, 2018, Halifax, NS, Canada. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3209280.3229115
  • 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.
  • Bodenreider O, Cornet R, Vreeman DJ. Recent Developments in Clinical Terminologies - SNOMED CT, LOINC, and RxNorm. Yearb Med Inform. 2018 Aug;27(1):129-139. doi: 10.1055/s-0038-1667077. Epub 2018 Aug 29.
  • Lowekamp B, Chen D, Yaniv Z, Yoo T. Scalable Simple Linear Iterative Clustering (SSLIC) Using a Generic and Parallel Approach. CoRR, 2018
  • 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.
  • Kim I, Thoma GR. Automated Identification of Potential Conflict-of-Interest in Biomedical Articles Using Hybrid Deep Neural Network. Proc. 14th Int’l Conf. Machine Learning and Data Mining (MLDM 2018), LNAI 10934, pp. 99-112, Newark, NJ, July 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.
  • Kilicoglu H, Rosemblat G, Malicki M, Ter Riet G. Automatic recognition of self-acknowledged limitations in clinical research literature. J Am Med Inform Assoc. 2018 Jul 1;25(7):855-861. doi: 10.1093/jamia/ocy038.
  • Kim I, Thoma GR. Automated Identification of Potential Conflict-of-Interest in Biomedical Articles Using Hybrid Deep Neural Network. Proc. 14th Int’l Conf. Machine Learning and Data Mining (MLDM 2018), LNAI 10934, pp. 99-112, Newark, NJ, July 2018.
  • 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.
  • McDonald CJ. Logical Observation Identifiers Names and Codes for In Vitro Diagnostic Test; Guidance for Industry and Food and Drug Administration Staff. Silver Spring, Md: Center for Devices and Radiological Health, FDA, 2018.
  • Yao S, Yu H, AliAkbarpour H, Seetharaman G, Palaniappan K. EpiX: A 3D Measurement Tool for Heritage, Archeology, and Aerial Photogrammetry Heritage Preservation, pp. 47-66, 2018.

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