Corpus ID: 53105774

Extractive Summarization of EHR Discharge Notes

@article{Alsentzer2018ExtractiveSO,
  title={Extractive Summarization of EHR Discharge Notes},
  author={Emily Alsentzer and A. Kim},
  journal={ArXiv},
  year={2018},
  volume={abs/1810.12085}
}
  • Emily Alsentzer, A. Kim
  • Published 2018
  • Computer Science, Mathematics
  • ArXiv
  • Patient summarization is essential for clinicians to provide coordinated care and practice effective communication. [...] Key Result We achieve an F1 score of 0.876, which indicates that this model can be employed to create a dataset for evaluation of extractive summarization methods.Expand Abstract

    Figures, Tables, and Topics from this paper.

    Explore Further: Topics Discussed in This Paper

    A Novel System for Extractive Clinical Note Summarization using EHR Data
    • 4
    • PDF
    Towards an Automated SOAP Note: Classifying Utterances from Medical Conversations
    • 1
    • PDF

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 26 REFERENCES
    Summarization of clinical information: A conceptual model
    • 74
    • PDF
    An automated knowledge-based textual summarization system for longitudinal, multivariate clinical data
    • 15
    Electronic Health Record Summarization over Heterogeneous and Irregularly Sampled Clinical Data
    • 3
    • PDF
    A Neural Attention Model for Abstractive Sentence Summarization
    • 1,516
    • PDF
    Assessing sentence scoring techniques for extractive text summarization
    • 196
    • PDF
    Text Summarization Techniques: A Brief Survey
    • 158
    • PDF
    Neural Networks for Joint Sentence Classification in Medical Paper Abstracts
    • 28
    • PDF