Hierarchical attention networks for information extraction from cancer pathology reports

OBJECTIVE: We explored how a deep learning (DL) approach based on hierarchical attention networks (HANs) can improve model performance for multiple information extraction tasks from unstructured cancer pathology reports compared to conventional methods that do not sufficiently capture syntactic and s...

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Bibliografiska uppgifter
I publikationen:J Am Med Inform Assoc
Huvudupphovsmän: Gao, Shang, Young, Michael T, Qiu, John X, Yoon, Hong-Jun, Christian, James B, Fearn, Paul A, Tourassi, Georgia D, Ramanthan, Arvind
Materialtyp: Artigo
Språk:Inglês
Publicerad: Oxford University Press 2018
Ämnen:
Research and Applications
Länkar:https://ncbi.nlm.nih.gov/pmc/articles/PMC7282502/
https://ncbi.nlm.nih.gov/pubmed/29155996
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamia/ocx131
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