Research on entity recognition of liver cancer electronic medical records based on RoBERTa-CRF

Corresponding author: Zhou Yi, zhouyi@mail.sysu.edu.cn

DOI: 10.12201/bmr.202303.00027

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  Abstract: Purpose Electronic medical records of liver cancer contain a large amount of medical knowledge, and most of the knowledge is in the form of unstructured data which is difficult to extract automatically. Knowledge extraction is important in the construction of clinical decision support systems and medical knowledge graphs in the area of liver cancer.Method This paper builds a named entity recognition model combined with RoBERTa algorithm and CRF algorithm and the model achieves excellent effect. The real data of self-labeled electronic medical records of liver cancer are used for model training and testing. Result RoBERTa-CRF model is better than other baseline models and has good entity recognition effect.

  Key words: electronic medical records of liver cancer; entity recognition; knowledge extraction; RoBERTa-CRF model

  Submit time: 22 March 2023

  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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  1	2022-12-02	bmr.202303.00027V1	Download

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