Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
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SHR Neuro Krebs Kardio Lipid Stoffw Microb
Miñarro-Giménez, JA; Hellrich, J; Schulz, S.
Acquisition of Character Translation Rules for Supporting SNOMED CT Localizations.
Stud Health Technol Inform. 2015; 210(12):597-601
PubMed
- Führende Autor*innen der Med Uni Graz
- Minarro-Gimenez Jose Antonio
- Co-Autor*innen der Med Uni Graz
- Schulz Stefan
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- Abstract:
- Translating huge medical terminologies like SNOMED CT is costly and time consuming. We present a methodology that acquires substring substitution rules for single words, based on the known similarity between medical words and their translations, due to their common Latin / Greek origin. Character translation rules are automatically acquired from pairs of English words and their automated translations to German. Using a training set with single words extracted from SNOMED CT as input we obtained a list of 268 translation rules. The evaluation of these rules improved the translation of 60% of words compared to Google Translate and 55% of translated words that exactly match the right translations. On a subset of words where machine translation had failed, our method improves translation in 56% of cases, with 27% exactly matching the gold standard.
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