Chemical-induced disease relation extraction via attention-based distant supervision
Abstract
Automatically understanding chemical-disease relations (CDRs) is crucial in various areas of biomedical research and health care. Supervised machine learning provides a feasible solution to automatically extract relations between biomedical entities from scientific literature, its success, however, heavily depends on large-scale biomedical corpora manually annotated with intensive labor and tremendous investment. We present an attention-based...
Paper Details
Title
Chemical-induced disease relation extraction via attention-based distant supervision
Published Date
Jul 22, 2019
Journal
Volume
20
Issue
1
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