A crowdsourcing workflow for extracting chemical-induced disease relations from free text.

ABSTRACT: Relations between chemicals and diseases are one of the most queried biomedical interactions. Although expert manual curation is the standard method for extracting these relations from the literature, it is expensive and impractical to apply to large numbers of documents, and therefore alternative methods are required. We describe here a crowdsourcing workflow for extracting chemical-induced disease relations from free text as part of the BioCreative V Chemical Disease Relation challenge. Five non-expert workers on the CrowdFlower platform were shown each potential chemical-induced disease relation highlighted in the original source text and asked to make binary judgments about whether the text supported the relation. Worker responses were aggregated through voting, and relations receiving

SUBMITTER: Li TS 

PROVIDER: S-EPMC4834205 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature