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Distant Supervision with Transductive Learning for Adverse Drug Reaction Identification from Electronic Medical Records
2017
Journal of Healthcare Engineering
Information extraction and knowledge discovery regarding adverse drug reaction (ADR) from large-scale clinical texts are very useful and needy processes. Two major difficulties of this task are the lack of domain experts for labeling examples and intractable processing of unstructured clinical texts. Even though most previous works have been conducted on these issues by applying semisupervised learning for the former and a word-based approach for the latter, they face with complexity in an
doi:10.1155/2017/7575280
pmid:29090077
pmcid:PMC5635478
fatcat:pdroxylgljaoragkwuqkucwq4q