Computer Science

Computer Science ›› 2024, Vol. 51 ›› Issue (11A): 240200041-7.doi: 10.11896/jsjkx.240200041

• Intelligent Computing • Previous Articles     Next Articles

Multi-task Learning Model for Text Feature Enhancement in Medical Field

GUO Ruiqiang1,2,3, JIA Xiaowen1, YANG Shilong1, WEI Qianqiang1   

  1. 1 School of Computer and Cyber Security,Hebei Normal University,Shijiazhuang 050024,China
    2 Hebei Provincial Engineering Research Center for Supply Chain Big Data Analytics & Data Security,Hebei Normal University,Shijiazhuang 050024,China
    3 Hebei Provincial Key Laboratory of Network and Information Security,Shijiazhuang 050024,China
  • Online:2024-11-16 Published:2024-11-13
  • About author:GUO Ruiqiang,born in 1974,Ph.D,professor,master supervisor,is a member of CCF(No.17546M).His main research interests include database system design,data mining,big data proces-sing.
  • Supported by:
    2023 Hebei Province Talent Introduction and Intelligence Innovation Platform(606080123003).

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Abstract: The recognition and standardization of medical named entities are the foundation for constructing high-quality medical knowledge graphs.This paper proposes a multi-task learning model based on text feature enhancement,aiming to address the issue of inadequate utilization of text features in existing models for medical entity recognition and standardization.The model incorporates word-level,character-level features,and contextual semantic information to enhance text representation.Through four hierarchical sub-tasks,it jointly models medical entity recognition and standardization tasks.Experiments indicate that the proposed model can learn common features for both entity recognition and entity standardization tasks,effectively improving the accuracy of learning.Satisfactory results are achieved on two datasets,NCBI and BC5CDR,with F1 scores for NER and NEN tasks 1.09%,91.02%;92.05%,92%,respectively.

Key words: Medical named entity recognition, Entity normalization, Multitask, Feature enhancement, Joint modeling

CLC Number: 

  • TP391
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