Clinical-Coder: Assigning interpretable ICD-10 codes to Chinese clinical notes

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Abstract

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.

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Cao, P., Yan, C., Fu, X., Chen, Y., Liu, K., Zhao, J., … Chong, W. (2020). Clinical-Coder: Assigning interpretable ICD-10 codes to Chinese clinical notes. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 294–301). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2020.acl-demos.33

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