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 | |
2020-07-05 | |
会议日期 | July 5 - 10, 2020 |
会议地点 | Online |
英文摘要 | 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. |
会议录出版者 | Association for Computational Linguistics |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/52146] |
专题 | 模式识别国家重点实验室_自然语言处理 |
作者单位 | 1.School of Artificial Intelligence, University of Chinese Academy of Sciences 2.Institute of Automation, Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Pengfei Cao,Chenwei Yan,Xiangling Fu,et al. Clinical-Coder: Assigning Interpretable ICD-10 Codes to Chinese Clinical Notes[C]. 见:. Online. July 5 - 10, 2020. |
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