基于Markov的Ⅱ型糖尿病预测技术研究

Prediction Technology of Type Ⅱ Diabetes Based on Markov Chain

  • 摘要: 针对糖尿病的发病率日益升高的问题,提出了一种基于马尔科夫模型的Ⅱ型糖尿病发病概率长时间预测方法. 该方法利用朴素贝叶斯算法计算风险等级概率向量,通过属性选择以后的属性子集空腹血糖值、体质系数、胆固醇、甘油三酯、腰围、性别、糖尿病家族史和年龄构建预测模型. 实验结果与阿基米德模型预测结果对比表明,该模型能够预测样本较长时期的Ⅱ型糖尿病发病概率,该预测方法简单、准确率高.

     

    Abstract: Diabetes is on the rise worldwide. Diabetes and its associated complications endanger the life of a large number of populations. Therefore, it is critical to predict and prevent the high incidence rate of diabetes. This paper proposes a method of long-term prediction of type Ⅱ diabetes incidence rate based on the Markov model. This method applies the naive Bayes arithmetic to calculate the probability vector of risk levels, and establishes the predicting model with selected property subsets of GLU, BMI, CHOL, TG, WAIST, SEX, DME and AGE. Compared with the predicted results obtained by using Archimedes model, the proposed method can predict long-term incidence rate of diabetes. The model recommended in this paper is proved to be simple and accurate for predicting the long-term incidence rate of type Ⅱ diabetes.

     

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