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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Foilsithe in:J Am Med Inform Assoc
Main Authors: Gao, Shang, Young, Michael T, Qiu, John X, Yoon, Hong-Jun, Christian, James B, Fearn, Paul A, Tourassi, Georgia D, Ramanthan, Arvind
Formáid: Artigo
Teanga:Inglês
Foilsithe: Oxford University Press 2018
Ábhair:
Research and Applications
Rochtain Ar Líne: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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