Knowledge Commons of Institute of Automation,CAS
Clinical-Coder: Assigning Interpretable ICD-10 Codes to Chinese Clinical Notes | |
Pengfei Cao![]() ![]() ![]() | |
2020-07-05 | |
会议名称 | The 58th Annual Meeting of the Association for Computational Linguistics |
会议日期 | July 5 - 10, 2020 |
会议地点 | Online |
出版者 | Association for Computational Linguistics |
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. |
收录类别 | EI |
七大方向——子方向分类 | 自然语言处理 |
国重实验室规划方向分类 | 语音语言处理 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/52146 |
专题 | 多模态人工智能系统全国重点实验室_自然语言处理 |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.School of Artificial Intelligence, University of 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]:Association for Computational Linguistics,2020. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
2020.acl-demos.33.pd(1388KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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