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Chemical-induced disease relation extraction via attention-based distant supervision
2019
BMC Bioinformatics
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. Results: We present an attention-based distant supervision paradigm for the
doi:10.1186/s12859-019-2884-4
fatcat:h2xnpdzlfffzrjqphubauszqp4