基于数据挖掘的藏医诊疗证候分型预测模型研究

Shiying Wang, Lei Zhang, Lu Wang, Cairang Nanjia, Xiaolan Zhu, Hong Li, Xiaoying Wang
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引用次数: 5

摘要

藏医在中国传统医学中占有重要地位。对于藏医科学的传承和疾病预防,主要方法是利用数据挖掘技术对用药和诊断规律进行总结和研究,目前尚处于早期阶段。本文首先利用聚类算法对临床诊疗数据和《四经》藏药处方进行分析,构建高原胃病标准知识库。其次,利用经典Apriori算法发现疾病症状和处方的关联特征。最后,结合患者个体特征和高原胃典型症状,在灰盒法的基础上,提出了一种基于水平距离判别的k近邻算法,实现了高原胃病(萎缩性胃炎)的藏药诊疗预测模型。结果表明,本文模型的准确率高达80.1%。
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Research on Syndrome Classification Prediction Model of Tibetan Medicine Diagnosis and Treatment Based on Data Mining
Tibetan Medicine plays an important role in traditional Chinese Medical Science. For the inheritance of Tibetan medical science and disease prevention, the main method is to summarize and study the medication and diagnostic rules by using data mining technology, which is still in the early stage. In this paper, firstly, a standard knowledge base for plateau stomach illness has been constructed by using clustering algorithm to analyze clinical diagnosis and treatment data and Tibetan medicine prescription that from "Four Medical Classics". Secondly, the classical Apriori algorithm is used to discover the associated features of disease symptoms and prescriptions. Finally, an ovel distance discriminant based K-nearest neighbor algorithm on the base of the Grey Box method is put forward to realize the Tibetan medicine diagnosis and treatment prediction model on the plateau stomach illness (Atrophic Gastritis) through combining the individual characteristics of patients and typical symptoms of plateau stomach. As a result, the model of this paper can achieve an accuracy as high as 80.1%.
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