This is a serious issue for low-resource language pairs and many specialized translation domains that are inherently limited in the amount of available supervised data.
Regularization of neural machine translation is still a significant problem, especially in low-resource settings.
Automatic post-editing (APE) systems aim to correct the systematic errors made by machine translators.
Nevertheless, the embeddings need to be retrained over datasets that are adequate for the domain, in order to adequately cover the domain-specific vocabulary.
Automated extraction of concepts from patient clinical records is an essential facilitator of clinical research.
Extraction of concepts present in patient clinical records is an essential step in clinical research.