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2019 | OriginalPaper | Buchkapitel

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

verfasst von : Wei Li, Zheng Yang

Erschienen in: Natural Language Processing and Chinese Computing

Verlag: Springer International Publishing

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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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Titel: Exploration on Generating Traditional Chinese Medicine Prescriptions from Symptoms with an End-to-End Approach
verfasst von: Wei Li
Zheng Yang
Verlag: Springer International Publishing
Buch: Natural Language Processing and Chinese Computing
Print ISBN: 978-3-030-32232-8

Electronic ISBN: 978-3-030-32233-5

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-32233-5_38

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