Building a PubMed knowledge graph | Scientific Data

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Measurement(s) textual entity • author information textual entity • funding source declaration textual entity • abstract • Biologic Entity Classification Technology Type(s) machine learning • computational modeling technique Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.12452597

Download PDF Subjects Communication and replication Data integration Data mining Abstract PubMed ® is an essential resource for the medical domain, but useful concepts are either difficult to extract or are ambiguous, which has significantly hindered knowledge discovery. To address this issue, we constructed a PubMed knowledge graph (PKG) by extracting bio-entities from 29 million PubMed abstracts, disambiguating author names, integrating funding data through the National Institutes of Health (NIH) ExPORTER, collecting affiliation history and educational background of authors from ORCID ® , an

Building a PubMed knowledge graph | Scientific Data

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