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Medical Named Entity Recognition Modelling Based on Remote Monitoring and Denoising

In: Clinical Chinese Named Entity Recognition in Natural Language Processing

Author

Listed:
  • Shuli Guo

    (Beijing Institute of Technology, National Key Lab of Autonomous Intelligent Unmanned Systems, School of Automation)

  • Lina Han

    (The Second Medical Center National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Department of Cardiology)

  • Wentao Yang

    (Beijing Institute of Technology, National Key Lab of Autonomous Intelligent Unmanned Systems, School of Automation)

Abstract

The electronic medical records (EMRs) are used in the public data set provided by Yidu Cloud to obtain remote data sets through remote supervision. For the obtained remote data set, in order to improve the reliability of the data set, the PU learning is adapted for denoising to reduce the negative impacts of mislabeled negative samples or unlabeled samples of the model. Finally, the negative samples and the pretraining models are used to extract a cancer information.

Suggested Citation

  • Shuli Guo & Lina Han & Wentao Yang, 2023. "Medical Named Entity Recognition Modelling Based on Remote Monitoring and Denoising," Springer Books, in: Clinical Chinese Named Entity Recognition in Natural Language Processing, chapter 0, pages 69-83, Springer.
    • Handle: RePEc:spr:sprchp:978-981-99-2665-7_5
    DOI: 10.1007/978-981-99-2665-7_5
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