Research on named entity identification method based on medical field

Runnan Zhou; Mingxuan Li; Peiguang Ruan; Tong Wang; Bing Gong; Wei Lv

doi:10.1117/12.2671403

28 April 2023 Research on named entity identification method based on medical field

Runnan Zhou, Mingxuan Li, Peiguang Ruan, Tong Wang, Bing Gong, Wei Lv

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126102R (2023) https://doi.org/10.1117/12.2671403
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

With the development of internet technology, more and more scholars are applying computer technology to research in the medical field. In this paper, we will investigate the named entity recognition method. Under the study of BERT-CRF model, we propose a named entity recognition model based on multi-task pre-training model with adversarial learning and network sharing and apply it to entity recognition in medical field with the aim of improving the accuracy of entity recognition in medical field. The model introduces multi-task joint learning and adversarial learning modules to improve the entity boundary effect and solve the noise problem of word boundary information, while achieving the purpose of information enhancement. On the CMeEE (Chinese Medical Entity Extraction) dataset, the model showed a significant improvement in accuracy, recall, and F1 score.

Citation Download Citation

Runnan Zhou, Mingxuan Li, Peiguang Ruan, Tong Wang, Bing Gong, and Wei Lv "Research on named entity identification method based on medical field", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126102R (28 April 2023); https://doi.org/10.1117/12.2671403

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