Bidirectional recurrent neural networks for medical event detection in electronic health records
A Jagannatha, H Yu - arXiv preprint arXiv:1606.07953, 2016 - arxiv.org
Sequence labeling for extraction of medical events and their attributes from unstructured text
in Electronic Health Record (EHR) notes is a key step towards semantic understanding of
EHRs. It has important applications in health informatics including pharmacovigilance and
drug surveillance. The state of the art supervised machine learning models in this domain
are based on Conditional Random Fields (CRFs) with features calculated from fixed context
windows. In this application, we explored various recurrent neural network frameworks and …
in Electronic Health Record (EHR) notes is a key step towards semantic understanding of
EHRs. It has important applications in health informatics including pharmacovigilance and
drug surveillance. The state of the art supervised machine learning models in this domain
are based on Conditional Random Fields (CRFs) with features calculated from fixed context
windows. In this application, we explored various recurrent neural network frameworks and …
[CITATION][C] Bidirectional recurrent neural networks for medical event detection in electronic health records.(2016)
A Jagannatha, H Yu - CoRR abs/1606.07953, 2016
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