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Research on Intelligent Traditional Chinese Medicine Prescription Model Based on Noisy-or Bayesian Network

机译:基于噪声或贝叶斯网络的智能中药处方模型研究

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Traditional Chinese Medicine (TCM) is the traditional medicine of China, which played an active role in the fight against the pneumonia caused by the novel coronavirus. How to make TCM benefit the general public, and to get the prescriptions of the prestigious Chinese physician without leaving home is a problem worth studying. This is of great significance for the inheritance of TCM. In this paper, an intelligent prescribing model is designed based on the nosiy-or Bayesian network. This model uses the correlation analysis method based on information entropy to obtain the network structure. The entire process greatly reduces the guidance of domain experts. The model uses the medical record data of a prestigious Chinese physician as training data, which can realize intelligent output Chinese medicine prescriptions with input symptom groups. The experimental results show a high accuracy of the model, and it can correctly simulate the diagnosis and treatment process of the prestigious Chinese physician.
机译:中药(TCM)是中国的传统医学,这在对抗新型冠状病毒引起的肺炎斗争中发挥了积极作用。如何使中医效益公众,并在不离开家的情况下获得着名中国医师的处方是一个值得学习的问题。这对TCM的遗传具有重要意义。在本文中,设计了一种基于Nosiy或贝叶斯网络的智能处方模型。该模型使用基于信息熵的相关分析方法来获得网络结构。整个过程大大降低了领域专家的指导。该模型使用着名的中国医师的医疗记录数据作为培训数据,可以实现具有输入症状组的智能输出中医处方。实验结果显示了该模型的高精度,可以正确模拟着名的中国医师的诊断和治疗过程。

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