| Document Date: 2012-11-12 06:12:53
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City SNOMED / Istanbul / Stockholm / / Company Studentlitteratur AB / Regional Ethical Review / / Country Turkey / Sweden / / / Event Product Recall / Product Issues / / Facility Karolinska University Hospital / Göteborg University / Stockholm University / / IndustryTerm readability solutions / pre-processing step / text mining / abbreviation detection algorithm / final algorithm / text mining models / / MarketIndex set 300 / / MedicalCondition automatic disorder / disorders / / Organization Stockholm University / Karolinska University Hospital / Göteborg University / Department of Linguistics / / Person Hanna Suominen / / Position physician / Automated Acronym Extractor / / Product results / / Technology Natural Language Processing / x-ray / 5 Conclusion Algorithms / rule-based algorithms / abbreviation detection algorithm / final algorithm / 5 b 3 Results The algorithm / / URL http /
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Initial Results in the Development of SCAN A Swedish Clinical Abbreviation Normalizer Niklas Isenius1, Sumithra Velupillai1, and Maria Kvist1, 2 1 2