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Semisupervised Learning Based Disease-Symptom and Symptom-Therapeutic Substance Relation Extraction from Biomedical Literature
2016
BioMed Research International
With the rapid growth of biomedical literature, a large amount of knowledge about diseases, symptoms, and therapeutic substances hidden in the literature can be used for drug discovery and disease therapy. In this paper, we present a method of constructing two models for extracting the relations between the disease and symptom and symptom and therapeutic substance from biomedical texts, respectively. The former judges whether a disease causes a certain physiological phenomenon while the latter
doi:10.1155/2016/3594937
pmid:27822473
pmcid:PMC5086401
fatcat:es7x7kqvbrafrdmartruixiq4y