Lung-Hao Lee, Yi Lu, Po-Han Chen, Po-Lei Lee, and Kuo-Kai Shyu.
In Proceedings of the 18th Workshop on Biomedical Natural Language Processing (BioNLP’19), pages 528-532.
Abstract
This study describes the model design of the NCUEE system for the MEDIQA challenge at the ACL-BioNLP 2019 workshop. We use the BERT (Bidirectional Encoder Representations from Transformers) as the word embedding method to integrate the BiLSTM (Bidirectional Long Short-Term Memory) network with an attention mechanism for medical text inferences. A total of 42 teams participated in natural language inference task at MEDIQA 2019. Our best accuracy score of 0.84 ranked the top-third among all submissions in the leaderboard.
