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

Tian Kang
Tian Kang
Youlan Tang
Youlan Tang
Casey Ta
Casey Ta

J. Am. Medical Informatics Assoc., pp. 812-823, 2021.

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摘要

This 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.

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