Table of Contents Author Guidelines Submit a Manuscript
Journal of Healthcare Engineering
Volume 2017 (2017), Article ID 3818302, 10 pages
https://doi.org/10.1155/2017/3818302
Research Article

Semantic Modeling for Exposomics with Exploratory Evaluation in Clinical Context

Jung-wei Fan,1,2,3 Jianrong Li,1,2,3 and Yves A. Lussier1,2,3,4

1Department of Medicine, The University of Arizona, Tucson, AZ, USA
2BIO5 Institute, The University of Arizona, Tucson, AZ, USA
3Center for Biomedical Informatics & Biostatistics, The University of Arizona, Tucson, AZ, USA
4Cancer Center, The University of Arizona, Tucson, AZ, USA

Correspondence should be addressed to Jung-wei Fan and Yves A. Lussier

Received 24 April 2017; Revised 26 June 2017; Accepted 30 July 2017; Published 30 August 2017

Academic Editor: Cui Tao

Copyright © 2017 Jung-wei Fan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. “The precision medicine initiative cohort program - building a research foundation for 21st century medicine, September 2016,” 2015, https://www.nih.gov/sites/default/files/research-training/initiatives/pmi/pmi-working-group-report-20150917-2.pdf.
  2. S. M. Langevin and K. T. Kelsey, “The fate is not always written in the genes: epigenomics in epidemiologic studies,” Environmental Molecular Mutagenesis, vol. 54, no. 7, pp. 533–541, 2013. View at Publisher · View at Google Scholar · View at Scopus
  3. C. P. Wild, “Complementing the genome with an ‘exposome’: the outstanding challenge of environmental exposure measurement in molecular epidemiology,” Cancer Epidemiology, Biomarkers & Prevention, vol. 14, no. 8, pp. 1847–1850, 2005. View at Publisher · View at Google Scholar · View at Scopus
  4. A. K. Manrai, Y. Cui, P. R. Bushel et al., “Informatics and data analytics to support exposome-based discovery for public health,” Annual Review Public Health Published Online First, vol. 38, pp. 279–294, 2017. View at Publisher · View at Google Scholar
  5. F. Martin Sanchez, K. Gray, R. Bellazzi, and G. Lopez-Campos, “Exposome informatics: considerations for the design of future biomedical research information systems,” Journal of the American Medical Informatics Association, vol. 21, no. 3, pp. 386–390, 2014. View at Publisher · View at Google Scholar · View at Scopus
  6. E. S. Chen, S. Manaktala, I. N. Sarkar, and G. B. Melton, “A multi-site content analysis of social history information in clinical notes,” in AMIA Annual Symposium Proceedings, pp. 227–236, Washington DC, USA, 2011.
  7. Y. Wang, E. S. Chen, S. Pakhomov et al., “Automated extraction of substance use information from clinical texts,” in AMIA Annual Symposium Proceedings, pp. 2121–2130, San Francisco, CA, USA, 2015.
  8. R. Aldekhyyel, E. S. Chen, S. Rajamani, Y. Wang, and G. B. Melton, “Content and quality of free-text occupation documentation in the electronic health record,” in AMIA Annual Symposium Proceedings, pp. 1708–1716, Chicago, IL, USA, 2016.
  9. K. M. Newton, P. L. Peissig, A. N. Kho et al., “Validation of electronic medical record-based phenotyping algorithms: results and lessons learned from the eMERGE network,” Journal of the American Medical Informatics Association, vol. 20, no. e1, pp. e147–e154, 2013. View at Publisher · View at Google Scholar · View at Scopus
  10. F. J. Martin-Sanchez and G. Lopez-Campos, “The new role of biomedical informatics in the age of digital medicine,” Methods of Information in Medicine, vol. 55, no. 5, pp. 392–402, 2016. View at Google Scholar
  11. F. T. Vertosick Jr., When the air Hits your Brain: Tales from Neurosurgery, W. W Norton & Company, 2008.
  12. S. Grape, P. Ravussin, A. Rossi, C. Kern, and L. A. Steiner, “Postoperative cognitive dysfunction,” Trends in Anaesthesia and Critical Care, vol. 2, no. 3, pp. 98–103, 2012. View at Publisher · View at Google Scholar · View at Scopus
  13. T. Wang, C. Gross, A. A. Desai et al., “Endothelial cell signaling and ventilator-induced lung injury: molecular mechanisms, genomic analyses, and therapeutic targets,” American Journal of Physiology-Lung Cellular and Molecular Physiology, vol. 312, no. 4, pp. L452–L476, 2017. View at Publisher · View at Google Scholar
  14. C. J. Mattingly, T. E. McKone, M. A. Callahan, J. A. Blake, and E. A. Hubal, “Providing the missing link: the exposure science ontology ExO,” Environmental Science & Technology, vol. 46, no. 6, pp. 3046–3053, 2012. View at Publisher · View at Google Scholar · View at Scopus
  15. D. A. B. Lindberg, B. L. Humphreys, and A. T. McCray, “The Unified Medical Language System,” Methods of Information in Medicine, vol. 32, pp. 281–291, 1993. View at Publisher · View at Google Scholar
  16. “IHTSDO. SNOMED CT. SNOMED CT, March 2017,” 2015, http://www.ihtsdo.org/snomed-ct/what-is-snomed-ct.
  17. A. McCray, “The UMLS Semantic Network,” in 13th Annual Symposium on Computer Application in Medical Care, pp. 503–507. View at Google Scholar
  18. A. T. McCray, A. Burgun, and O. Bodenreider, “Aggregating UMLS semantic types for reducing conceptual complexity,” in Studies in Health Technology and Informatics, pp. 216–220. View at Publisher · View at Google Scholar · View at Scopus
  19. W. W. Chapman, P. M. Nadkarni, L. Hirschman, L. W. D’Avolio, G. K. Savova, and O. Uzuner, “Overcoming barriers to NLP for clinical text: the role of shared tasks and the need for additional creative solutions,” Journal of the American Medical Informatics Association, vol. 18, no. 5, pp. 540–543, 2011. View at Publisher · View at Google Scholar · View at Scopus
  20. Ö. Uzuner, Y. Luo, and P. Szolovits, “Evaluating the state-of-the-art in automatic de-identification,” Journal of the American Medical Informatics Association, vol. 14, no. 5, pp. 550–563, 2007. View at Publisher · View at Google Scholar · View at Scopus
  21. A. R. Aronson and F.-M. Lang, “An overview of MetaMap: historical perspective and recent advances,” Journal of the American Medical Informatics Association, vol. 17, no. 3, pp. 229–236, 2010. View at Publisher · View at Google Scholar · View at Scopus
  22. “The brat rapid annotation tool: online environment for collaborative text annotation, March 2017,” 2012, http://brat.nlplab.org.
  23. X. Wang, G. Hripcsak, and C. Friedman, “Characterizing environmental and phenotypic associations using information theory and electronic health records,” BMC Bioinformatics, vol. 10, Supplement 9, p. S13, 2009. View at Publisher · View at Google Scholar
  24. A. Turchin, M. Shubina, E. Breydo, M. L. Pendergrass, and J. S. Einbinder, “Comparison of information content of structured and narrative text data sources on the example of medication intensification,” Journal of the American Medical Informatics Association, vol. 16, no. 3, pp. 362–370, 2009. View at Publisher · View at Google Scholar · View at Scopus
  25. J. R. Moon, M. M. Glymour, S. V. Subramanian, M. Avendaño, and I. Kawachi, “Transition to retirement and risk of cardiovascular disease: prospective analysis of the US health and retirement study,” Social Science & Medicine, vol. 75, no. 3, pp. 526–530, 2012. View at Publisher · View at Google Scholar · View at Scopus
  26. A. Daoulah, M. N. Alama, O. E. Elkhateeb et al., “Widowhood and severity of coronary artery disease: a multicenter study,” Coronary Artery Dis Published Online First, vol. 28, no. 2, pp. 98–103, 2016. View at Publisher · View at Google Scholar · View at Scopus