1 code implementation • NAACL (ClinicalNLP) 2022 • Matías Rojas, Jocelyn Dunstan, Fabián Villena
To validate the quality of the contextual representations retrieved from our model, we tested them on four named entity recognition datasets belonging to the clinical and biomedical domains.
no code implementations • EMNLP (ClinicalNLP) 2020 • Pablo Báez, Fabián Villena, Matías Rojas, Manuel Durán, Jocelyn Dunstan
The best results were achieved by using a biLSTM-CRF architecture using word embeddings trained over Spanish Wikipedia together with clinical embeddings computed by the group.
no code implementations • 9 Jul 2023 • Fabián Villena, Matías Rojas, Felipe Arias, Jorge Pacheco, Paulina Vera, Jocelyn Dunstan
This system could be a support tool for health professionals, optimizing the coding and management process.
1 code implementation • ACM Transactions on Computing for Healthcare 2022 • Pablo Báez, Felipe Bravo-Marquez, Jocelyn Dunstan, Matías Rojas, Fabián Villena
The annotated corpus, clinical word embeddings, annotation guidelines, and neural models are freely released to the community.