Training and intrinsic evaluation of lightweight word embeddings for the clinical domain in Spanish.

ABSTRACT: Resources for Natural Language Processing (NLP) are less numerous for languages different from English. In the clinical domain, where these resources are vital for obtaining new knowledge about human health and diseases, creating new resources for the Spanish language is imperative. One of the most common approaches in NLP is word embeddings, which are dense vector representations of a word, considering the word's context. This vector representation is usually the first step in various NLP tasks, such as text classification or information extraction. Therefore, in order to enrich Spanish language NLP tools, we built a Spanish clinical corpus from waiting list diagnostic suspicions, a biomedical corpus from medical journals, and term sequences sampled from the Unified Medical Language Syste

SUBMITTER: Chiu C 

PROVIDER: S-EPMC9533099 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature