Medizinische Universität Graz - Research portal

Go directly to the nagivation.
Go directly to the content.

Navigation/Search

Selected Publication:

SHR Neuro Cancer Cardio Lipid Metab Microb

Pomares-Quimbaya, A; López-Úbeda, P; Schulz, S.
Transfer Learning for Classifying Spanish and English Text by Clinical Specialties.
Stud Health Technol Inform. 2021; 281: 377-381. Doi: 10.3233/SHTI210184
PubMed FullText FullText_MUG

Co-authors Med Uni Graz: Schulz Stefan
Altmetrics:
Dimensions Citations:
Plum Analytics:
Scite (citation analytics):
Abstract:: Transfer learning has demonstrated its potential in natural language processing tasks, where models have been pre-trained on large corpora and then tuned to specific tasks. We applied pre-trained transfer models to a Spanish biomedical document classification task. The main goal is to analyze the performance of text classification by clinical specialties using state-of-the-art language models for Spanish, and compared them with the results using corresponding models in English and with the most important pre-trained model for the biomedical domain. The outcomes present interesting perspectives on the performance of language models that are pre-trained for a particular domain. In particular, we found that BioBERT achieved better results on Spanish texts translated into English than the general domain model in Spanish and the state-of-the-art multilingual model.
Find related publications in this database (using NLM MeSH Indexing): Female - administration & dosage; Language - administration & dosage; Learning - administration & dosage; Machine Learning - administration & dosage; Multilingualism - administration & dosage; Natural Language Processing - administration & dosage