UMLS-based data augmentation for natural language processing of clinical research literature

ConclusionsThis study presents a UMLS-based data augmentation method, UMLS-EDA. It is effective at improving deep learning models for both NER and sentence classification, and contributes original insights for designing new, superior deep learning approaches for low-resource biomedical domains.
Source: Journal of the American Medical Informatics Association - Category: Information Technology Source Type: research