CASIA OpenIR  > 多模态人工智能系统全国重点实验室  > 自然语言处理
Clinical-Coder: Assigning Interpretable ICD-10 Codes to Chinese Clinical Notes
Pengfei Cao; Chenwei Yan; Xiangling Fu; Yubo Chen; Kang Liu; Jun Zhao; Shengping Liu; Weifeng Chong
Conference NameThe 58th Annual Meeting of the Association for Computational Linguistics
Conference DateJuly 5 - 10, 2020
Conference PlaceOnline
PublisherAssociation for Computational Linguistics

In this paper, we introduce Clinical-Coder, an online system aiming to assign ICD codes to Chinese clinical notes. ICD coding has been a research hotspot of clinical medicine, but the interpretability of prediction hinders its practical application. We exploit a Dilated Convolutional Attention network with N-gram Matching Mechanism (DCANM) to capture semantic features for non-continuous words and continuous n-gram words, concentrating on explaining the reason why each ICD code to be predicted. The experiments demonstrate that our approach is effective and that our system is able to provide supporting information in clinical decision making.

Indexed ByEI
Sub direction classification自然语言处理
planning direction of the national heavy laboratory语音语言处理
Paper associated data
Document Type会议论文
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.School of Artificial Intelligence, University of Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Pengfei Cao,Chenwei Yan,Xiangling Fu,et al. Clinical-Coder: Assigning Interpretable ICD-10 Codes to Chinese Clinical Notes[C]:Association for Computational Linguistics,2020.
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