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Automatic Prediction of Semantic Labels for French Medical Terms
Thierry Hamon, Natalia Grabar
868 - 869
10.3233/SHTI220610
Research Article
Studies in Health Technology and Informatics
Volume 294: Challenges of Trustable AI and Added-Value on Health
Abstract

We address the problem of semantic labeling of terms in two French medical corpora with the subset of the UMLS. We perform two experiments relying on the structure of words and terms, and on their context: 1) the semantic label of already identified terms is predicted; 2) the terms are detected in raw texts and their semantic label is predicted. Our results show over 0.90 F-measure.

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