This chapter gives a short introduction of the research area of clinical text mining.
- Allvin, H., Carlsson, E., Dalianis, H., Danielsson-Ojala, R., Daudaravicius, V., Hassel, M., et al. (2011). Characteristics of Finnish and Swedish intensive care nursing narratives: A comparative analysis to support the development of clinical language technologies. Journal of Biomedical Semantics, 2(Suppl 3), 1–11.CrossRefGoogle Scholar
- Dalianis, H. (2014). Clinical text retrieval - An overview of basic building blocks and applications. In Professional Search in the Modern World (pp. 147–165). Berlin: Springer.Google Scholar
- Dalianis, H., Hassel, M., & Velupillai, S. (2009). The Stockholm EPR Corpus-characteristics and some initial findings. In Proceedings of ISHIMR 2009, Evaluation and Implementation of e-Health and Health Information Initiatives: International Perspectives. 14th International Symposium for Health Information Management Research (pp. 243–249).Google Scholar
- Ducel, G., Fabry, J., & Nicolle, L. (Eds.). (2002). Prevention of Hospital Acquired Infections: A Practical Guide., 2nd edn. World Health Organization. http://www.who.int/csr/resources/publications/drugresist/WHO_CDS_CSR_EPH_2002_12/en/. Accessed 11 Jan 2018.
- Groopman, J. E. (2007). How Doctors Think. New York: Houghton Mifflin Company.Google Scholar
- Meystre, S. M., Savova, G. K., Kipper-Schuler, K. C., & Hurdle, J. F. (2008). Extracting information from textual documents in the electronic health record: A review of recent research. Yearbook of Medical Informatics, 35, 128–144.Google Scholar
- Névéol, A., Dalianis, H., Savova, G., & Zweigenbaum, P. (2018). Clinical natural language processing in languages other than english: opportunities and challenges. Journal of Biomedical Semantics, 9(12), 1–13.Google Scholar
- Pratt, A. W., & Pacak, M. G. (1969). Automated processing of medical English. In Proceedings of the 1969 Conference on Computational Linguistics (pp. 1–23). Association for Computational Linguistics.Google Scholar
- Spasić, I., Livsey, J., Keane, J. A., & Nenadić, G. (2014). Text mining of cancer-related information: Review of current status and future directions. International Journal of Medical Informatics, 83(9), 605–623. http://dx.doi.org/10.1016/j.ijmedinf.2014.06.009. Accessed 11 Jan 2018.CrossRefGoogle Scholar
- Velupillai, S., Dalianis, H., Hassel, M., & Nilsson, G. H. (2009). Developing a standard for de-identifying electronic patient records written in Swedish: Precision, recall and F-measure in a manual and computerized annotation trial. International Journal of Medical Informatics, 78(12), e19–e26.CrossRefGoogle Scholar
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