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  • 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.
  • 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.
  • 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.
  • Goss FR, Lai KH, Topaz M, Acker WW, Kowalski L, Plasek JM, Blumenthal KG, Seger DL, Slight SP, Fung KW, Chang FY, Bates DW, Zhou L. A value set for documenting adverse reactions in electronic health records. J Am Med Inform Assoc. 2018 Jun 1;25(6):661-669. doi: 10.1093/jamia/ocx139.
  • Yaniv Z, Lowekamp B, Johnson HJ, Beare R. SimpleITK Image-Analysis Notebooks: a Collaborative Environment for Education and Reproducible Research. J Digit Imaging. 2018 Jun;31(3):290-303. doi: 10.1007/s10278-017-0037-8.
  • 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.
  • Vreeman DJ, Abhyankar S, McDonald CJ. Re: Unit conversions between LOINC codes Published June 19, 2017 [Letter]. J Am Med Inform Assoc. 2018 May 1;25(5):614-615. doi: 10.1093/jamia/ocx087.
  • Edinger T, Demner-Fushman D, Cohen AM, Bedrick S, Hersh W. Evaluation of Clinical Text Segmentation to Facilitate Cohort Retrieval. AMIA Annu Symp Proc. 2018 Apr 16;2017:660-669. eCollection 2017.
  • Fung K, Xue Z, Ameye F, Gutierrez AR, D'Have A. Achieving Logical Equivalence between SNOMED CT and ICD-10-PCS Surgical Procedures. AMIA Annu Symp Proc. 2018 Apr 16;2017:724-733. eCollection 2017.
  • 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.
  • Bodenreider O. Evaluating the Quality and Interoperability of Biomedical Terminologies Technical Report to the LHNCBC Board of Scientific Counselors April 2018
  • Huser V, Shmueli-Blumberg D. Data sharing platforms for de-identified data from human clinical trials. Clin Trials. 2018 Apr 1:1740774518769655. doi: 10.1177/1740774518769655. [Epub ahead of print]
  • 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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