Ethics and Privacy of Patient Records for Clinical Text Mining Research
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This chapter discusses ethical issues while working with sensitive material such as patient records, how to apply for ethical permission, the safe storage of sensitive data and other privacy-related topics.
- Alfalahi, A., Brissman, S., & Dalianis, H. (2012). Pseudonymisation of personal names and other PHIs in an annotated clinical Swedish corpus. In Third Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM 2012) Held in Conjunction with LREC 2012, May 26, Istanbul (pp. 49–54).Google Scholar
- Almgren, S., & Pavlov, S. (2016). Semi-supervised Named Entity Recognition of Medical Entities in Swedish. Master’s thesis, Department of Computer Science and Engineering, Chalmers University of Technology.Google Scholar
- Almgren, S., Pavlov, S., & Mogren, O. (2016). Named entity recognition in Swedish health records with character-based deep bidirectional LSTMs. In Proceedings of the Fifth Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM 2016), Held in Conjunction with Coling 2016 (pp. 30–29).Google Scholar
- Antfolk, A., & Branting, R. (2016). Pseudonymisering av platser i patient-journaltexter (In Swedish). Bachelor’s thesis, Department of Computer and Systems Sciences, Stockholm University.Google Scholar
- Björkegren, A. (2011). Pseudonymisering av digitala patientjournaler (In Swedish). Bachelor’s thesis, Department of Computer and Systems Sciences, Stockholm University.Google Scholar
- Carrell, D., Malin, B., Aberdeen, J., Bayer, S., Clark, C., Wellner, B., et al. (2013). Hiding in plain sight: Use of realistic surrogates to reduce exposure of protected health information in clinical text. Journal of the American Medical Informatics Association, 20(2), 342–348.CrossRefGoogle Scholar
- Dalianis, H., & Boström, H. (2012). Releasing a Swedish clinical corpus after removing all words–de-identification experiments with conditional random fields and random forests. In Proceedings of the Third Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM 2012) Held in Conjunction with LREC (pp. 45–48).Google Scholar
- Dalianis, H., Henriksson, A., Kvist, M., Velupillai, S., & Weegar, R. (2015). HEALTH BANK–A workbench for data science applications in healthcare. In J. Krogstie, G. Juel-Skielse, & V. Kabilan (Eds.), Proceedings of the CAiSE-2015 Industry Track Co-located with 27th Conference on Advanced Information Systems Engineering (CAiSE 2015), Stockholm, Sweden, June 11, 2015, CEUR (Vol. 1381, pp. 1–18). https://doi.org/urn:nbn:de:0074-1381-0E.
- Health Insurance Portability and Accountability Act (HIPAA). (2003). U.S. Department of Health and Human Services. http://www.cdc.gov/mmwr/preview/mmwrhtml/m2e411a1.htm. Accessed 11 Jan 2018.
- Henriksson, A., Kvist, M., & Dalianis, H. (2017a). Prevalence estimation of protected health information in Swedish clinical text. Studies in Health Technology and Informatics, Vol 235, pp. 216–220.Google Scholar
- Henriksson, A., Kvist, M., & Dalianis, H. (2017b). Detecting protected health information in heterogeneous clinical notes. Studies in Health Technology and Informatics, Vol 245, pp. 394–397.Google Scholar
- Meystre, S. M., Shen, S., Hofmann, D., & Gundlapalli, A. V. (2014). Can physicians recognize their own patients in de-identified notes? In MIE-Medical Informatics Europe (pp. 778–782).Google Scholar
- Suominen, H. (2012). Towards an international electronic repository and virtual laboratory of open data and open-source software for telehealth research: Comparison of international, Australian and Finnish privacy policies. Studies in Health Technology and Informatics, 182, 153–160.Google Scholar
- Suominen, H., Müller, H., Ohno-Machado, L., Salanterä, S., Schreier, G., & Hanlen, L. (2017). Prerequisites for International Exchanges of Health Information: Comparison of Australian, Austrian, Finnish, Swiss, and US Privacy Policies. Studies in Health Technology and Informatics, Vol 245, pp. 1312.Google Scholar
- Sweeney, L. (1996). Replacing personally-identifying information in medical records, the scrub system. In Proceedings of the AMIA Annual Fall Symposium (p. 333). American Medical Informatics Association.Google 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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