Chemical-induced disease relation extraction via attention-based distant supervision.
Journal:
BMC bioinformatics
Published Date:
Jul 22, 2019
Abstract
BACKGROUND: 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.