Correlation Between Diabetes And Body Composition Of Based On Decision Tree And Neural Network

The existing correlation analysis between diabetes and body composition is mostly based on statistical analysis methods. Due to the dependency on experiences and constraints of selected samples, it is difficult to reflect the relationship between physiological and biochemical indicators. Therefore, a method for correlation analysis of diabetes and body composition is proposed in this paper based on decision tree and neural network. On one hand, the decision tree is used to identify the correlation that is easier to find. On the other hand, the neural network with the self-learning advantage is used to further study some uncertainties. The analysis on experimental data shows that this proposed method could effectively simplify the analysis process of the correlation between diabetes and body composition, improve the analysis accuracy, and provide new ideas for the diagnosis and treatment of diabetes.