2020
DOI: 10.1109/access.2020.2992130
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Investigating of Disease Name Normalization Using Neural Network and Pre-Training

Abstract: Normalizing disease names is a crucial task for biomedical and healthcare domains. Previous work explored various approaches, including rules, machine learning and deep learning, which focused on only one approach or one model. In this study, we systematically investigated the performances of various neural models and the effects of different features. Our investigation was performed on two benchmark datasets, namely the NCBI disease corpus and the BioCreative V Chemical Disease Relation (BC5CDR) corpus. The c… Show more

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Cited by 3 publications
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