Method for Extracting Data Elements from Chinese Electronic Medical Records

Corresponding author: Guo Weijia, guowj2022@163.com

DOI: 10.12201/bmr.202404.00038

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  Abstract: Purpose/Significance Extracting data elements that comply with national standards from EMR (Electronic Medical Records) can help to achieve fine-grained sharing of EMR data. Method/Process This paper proposes a method for extracting data elements from Chinese EMRs. Firstly, it uses the ALBERT, BILSTM and CRF models to perform sequence labeling on EMRs, and generates a set of candidate data elements based on labeling results. Then, for any candidate data element, its contextual information is collected to form an enhanced key vector. Finally, the similarity between the vector and the standard vector is calculated to determine whether the candidate data element is valid. Result/Conclusion The results show that the F1 value is 90.32%, indicating good performance. The shortcomings are the small size of the experimental dataset and the uneven distribution of data element types.

  Key words: Electronic medical record; Data element; ALBERT; Sequence labeling; Token vector

  Submit time: 26 April 2024

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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• ID	Submit time	Number	Download
  2	2023-12-14	bmr.202404.00038V2	Download
  1	2023-12-14	bmr.202404.00038V1	Download

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