Translating Medical Words by Analogy

Term translation has become a recurring need in medical informatics. This creates an interest for robust methods which can translate medical words in various languages. We propose a novel, analogy-based method to generate word translations. It relies on a partial bilingual lexicon and solves bilingual analogical equations to create candidate translations. To evaluate the potential of this method, we tested it on several datasets for five language pairs (10 translation directions). At best could the approach propose a correct translation for up to 67.9% of the input words, with a precision of up to 80.2% depending on the number of selected candidates. We compare it to previous methods including word alignment in parallel corpora and edit distance to a list of words, and show that these methods can complement each other.