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CCF International Conference on Natural Language Processing and Chinese Computing

NLPCC 2019: Natural Language Processing and Chinese Computing pp 486–498Cite as

Exploration on Generating Traditional Chinese Medicine Prescriptions from Symptoms with an End-to-End Approach

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11838))

Abstract

Traditional Chinese Medicine (TCM) is an influential form of medical treatment in China and surrounding areas. In this paper, we propose a TCM prescription generation task that aims to automatically generate a herbal medicine prescription based on textual symptom descriptions. Sequence-to-sequence (seq2seq) model has been successful in dealing with sequence generation tasks. We explore a potential end-to-end solution to the TCM prescription generation task using seq2seq models. However, experiments show that directly applying seq2seq model leads to unfruitful results due to the repetition problem. To solve the problem, we propose a novel decoder with coverage mechanism and a soft loss function. The experimental results demonstrate the effectiveness of the proposed approach. Judged by professors who excel in TCM, the generated prescriptions are rated 7.3 out of 10, which means that the model can indeed help with the prescribing procedure in real life.

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Notes

  1. 1.

    The resources will be published online.

  2. 2.

    http://www.hhjfsl.com/fang/.

  3. 3.

    “ ” (radix bupleuri), “ ” (the root of kudzu vine) can be roughly matched with “ ” (Aversion to wind, fever, sweating, headache), “ ” (Glycyrrhiza), “ ” (dried tangerine or orange peel), “ ” (Platycodon grandiflorum) can be roughly matched with “ ” (nasal obstruction, dry throat, white tongue coating, not thirsty), “ ” (Ligusticum wallichii) can be used to treat the symptom of “ ” (headache).

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Author information

Authors and Affiliations

  1. MOE Key Lab of Computational Linguistics, School of EECS, Peking University, Beijing, China

    Wei Li

  2. School of Traditional Chinese Medicine, Beijing Univeristy of Chinese Medicine, Beijing, China

    Zheng Yang

Authors
  1. Wei Li
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  2. Zheng Yang
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Corresponding author

Correspondence to Wei Li .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Jie Tang

  2. National University of Singapore, Singapore, Singapore

    Min-Yen Kan

  3. Peking University, Beijing, China

    Dongyan Zhao

  4. Peking University, Beijing, China

    Sujian Li

  5. Zhengzhou University, Zhengzhou, China

    Hongying Zan

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Cite this paper

Li, W., Yang, Z. (2019). Exploration on Generating Traditional Chinese Medicine Prescriptions from Symptoms with an End-to-End Approach. In: Tang, J., Kan, MY., Zhao, D., Li, S., Zan, H. (eds) Natural Language Processing and Chinese Computing. NLPCC 2019. Lecture Notes in Computer Science(), vol 11838. Springer, Cham. https://doi.org/10.1007/978-3-030-32233-5_38

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  • DOI: https://doi.org/10.1007/978-3-030-32233-5_38

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-32232-8

  • Online ISBN: 978-3-030-32233-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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