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Named Entity Recognition for Chinese Cancer Electronic Health Records—Development and Evaluation of a Domain-Specific BERT Model: Quantitative Study

Named Entity Recognition for Chinese Cancer Electronic Health Records—Development and Evaluation of a Domain-Specific BERT Model: Quantitative Study

Chen et al [6] constructed a hybrid model combining MC-BERT, Bi LSTM, CNN, MHA, and CRF to achieve NER in Chinese EHRs. Most of these studies primarily applied their deep learning models to publicly available datasets such as CCKS2017 and CCKS2019, without further testing them on specific medical departments or diseases. Existing research indicates that using domain-specific text as training data, as opposed to general language models, can yield better performance.

Junbai Chen, Butian Zhao, Xiaohan Tian, Zhengkai Zou, Ruojia Wang, Jiarui Wu, Songxing Du, Fengying Guo

JMIR Med Inform 2025;13:e76912