Published on in Vol 4, No 2 (2018): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9361, first published .
Clinical Relation Extraction Toward Drug Safety Surveillance Using Electronic Health Record Narratives: Classical Learning Versus Deep Learning

Clinical Relation Extraction Toward Drug Safety Surveillance Using Electronic Health Record Narratives: Classical Learning Versus Deep Learning

Clinical Relation Extraction Toward Drug Safety Surveillance Using Electronic Health Record Narratives: Classical Learning Versus Deep Learning

Authors of this article:

Tsendsuren Munkhdalai1 Author Orcid Image ;   Feifan Liu1 Author Orcid Image ;   Hong Yu2, 3 Author Orcid Image

Journals

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  14. Li F, Liu W, Yu H. Extraction of Information Related to Adverse Drug Events from Electronic Health Record Notes: Design of an End-to-End Model Based on Deep Learning. JMIR Medical Informatics 2018;6(4):e12159 View
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  20. Mitra A, Rawat B, McManus D, Yu H. Relation Classification for Bleeding Events From Electronic Health Records Using Deep Learning Systems: An Empirical Study. JMIR Medical Informatics 2021;9(7):e27527 View
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  29. Yang L, Huang X, Wang J, Yang X, Ding L, Li Z, Li J. Identifying stroke-related quantified evidence from electronic health records in real-world studies. Artificial Intelligence in Medicine 2023;140:102552 View
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Books/Policy Documents

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