Cited by 314Machine Learning in HealthcareBiomedical Text Mining and OntologiesTopic Modeling

Bidirectional RNN for Medical Event Detection in Electronic Health Records

Open access
Jagannatha, Abhyuday N, Yu, Hong·2016·Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Abstract

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 recurrent neural network frameworks and show that they significantly out-performed the CRF models.

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  • Deep Learning approaches have gained popularity to overcome challenges faced by traditional NLP approaches in extracting information from EHR.

    “To overcome challenges faced by traditional NLP approaches in extracting information from EHR, recently, Deep Learning (DL approaches have gained popularity [45].”

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Research works printed but not linked: 2

  1. Bergstra James Breuleux Olivier Bastien Frdric Lamblin Pascal Pascanu Razvan Desjardins Guillaume Turian Joseph Warde-Farley David Bengio Yoshua 2010 Theano: a CPU and GPU math expression compiler Proceedings of the Python for Scientific Computing Conference (SciPy)
  2. Li Z Cao Y Antieau L Agarwal S Zhang Q Yu H 2009 Extracting Medication Information from Patient Discharge Summaries Third i2b2 Shared-Task Workshop

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Authors
Jagannatha, A. N., & Yu, H.
Affiliations
Edith Nourse Rogers Memorial Veterans Hospital (US)
Venue
Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Published
2016
Volume
2016
Pages
473-482
OpenAlex
W2469314752
Cited by
314
References
30
Citations by year
2026: 4 · 2025: 15 · 2024: 14 · 2023: 28 · 2022: 28 · 2021: 36 · 2020: 58 · 2019: 68 · 2018: 40 · 2017: 17 · 2016: 6
FWCI
23.53
Type
conference paper
Language
en
Open access
Licence
cc-by
Locations
  • Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • U.S. Department of Veterans Affairs (I01 HX001457)
  • National Heart, Lung, and Blood Institute (R01HL125089)
  • National Cancer Institute (U01CA180975)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
  • Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
Keywords
bidirectional recurrent neural network, electronic health records, sequence labeling, clinical text annotation, conditional random fields, pharmacovigilance, unstructured clinical notes

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