Abstract
AbstractKey assertions are extracted from “conclusions” sections of PubMed abstracts andconverted into Semantic Web / Linked Data format. The results are made accessible viafiles, a SPARQL endpoint, and a faceted search interface. Conclusion sections areidentified as valuable resources for machine-augmented key assertion identification andintegration in the biomedical domain. Results are discussed and opportunities for futurework and cooperation are highlighted.
Highlights
A common challenge faced by biomedical researchers and clinicians is to quickly get an overview of publications for a certain biomedical topic, and to identify relevant, valid facts, research trends and contradictory findings
„CONCLUSIONS: This study shows that Seasonal affective disorder (SAD) is effectively treated with ...“
„CONCLUSIONS: This study shows that Seasonal affective disorder is effectively treated with ...“
Summary
A common challenge faced by biomedical researchers and clinicians is to quickly get an overview of publications for a certain biomedical topic, and to identify relevant, valid facts, research trends and contradictory findings. One search strategy to address this challenge is to do a PubMed search, look at the first few dozen results and quickly skim over the conclusions in the abstracts of the most recent publications This only gives a shallow summary of the contents of each publication, and it makes the judgment of the validity of each claim rather dubious. This search strategy is useful to get an overview of relevant findings, to see how different biological phenomena relate to each other, and to identify starting points for further investigation. While the conclusion sections contain lots of these abbreviated forms that tend to be unintelligible when only the conclusion sections are viewed in isolation, e.g.:
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