Abstract

The purpose of this study is to extract similar term definitions used in the terminology of Japanese medical device adverse events. We employed Levenshtein and Jaro-Winkler distances as edit distances and Skip-gram, continuous-bag of words, and fast text to produce distributed representations in Word2Vec. A comparison of the accuracies of the models showed that Levenshtein distance had higher specificity whereas Skip-gram had higher sensitivity as compared to the other models.

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