| Issue |
MATEC Web Conf.
Volume 336, 2021
2020 2nd International Conference on Computer Science Communication and Network Security (CSCNS2020)
|
|
|---|---|---|
| Article Number | 07018 | |
| Number of page(s) | 6 | |
| Section | Intelligence Algorithms and Application | |
| DOI | https://doi.org/10.1051/matecconf/202133607018 | |
| Published online | 15 February 2021 | |
Risk prediction of early diabetes mellitus based on combination model
1 Sichuan Agricultural University, Dujiangyan, China
* Corresponding author: liucheng@sicau.edu.cn
Aiming at the current low pre-diabetes detection rate, this paper proposes a PSO-SVM model to assist doctors in identifying the risk of patients with pre-diabetes. The paper uses the Support Vector Machine as the verification algorithm, takes the radial basis kernel as the kernel function, uses the adaptive Particle Swarm Optimization algorithm to optimize the penalty factor and kernel parameters of the Support Vector Machine, and establishes a PSO-SVM model, finally compares the model with Neural Network, Logistic Regression, and Naive Bayes model, and use Sensitivity, Specificity indicators and ROC curve to evaluate model performance. Empirical analysis proves that the combined model proposed in this paper can effectively identify the risk of patients with prediabetes.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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