Automated web annotator of biomedical entities in spanish language.

In Natural Language Processing (NLP) and supervised machine learning, the scarcity of labeled corpora results in poor performance of machine learning models. In the medical domain, there are also fewer labeled corpora in Spanish than in English. We propose a method to identify biomedical entities in...

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Bibliographic Details
Authors: Morejón Corrales, Samiel Andrés, Iza Iza, Josselyn Libelia
Format: article
Status:Published version
Publication Date:2022
Country:Ecuador
Institution:Universidad de las Fuerzas Armadas
Repository:Repositorio Universidad de las Fuerzas Armadas
Language:English
OAI Identifier:oai:repositorio.espe.edu.ec:21000/33602
Online Access:http://repositorio.espe.edu.ec/handle/21000/33602
Access Level:Open access
Keyword:SISTEMAS WEB
ALINEACIÓN AUTOMÁTICA
PROGRAMACIÓN NEUROLINGUÍSTICA
Description
Summary:In Natural Language Processing (NLP) and supervised machine learning, the scarcity of labeled corpora results in poor performance of machine learning models. In the medical domain, there are also fewer labeled corpora in Spanish than in English. We propose a method to identify biomedical entities in Spanish-language clinical texts, through automatic translation and word alignment, by translating the source text (Spanish) to the target text (English), then labeling the target text with automatic biomedical entity taggers, and finally projecting the biomedical entities from the target text to the corresponding text sections in the source text by means of word alignment generated in the translation process. This is done with the objective of annotating the source text with English language tools (automatic annotators). As a result, an efficient method capable of processing and annotating biomedical entities in the Spanish language with high precision is obtained, since it integrates several automatic annotators in a single web system.