Investigation of diabetic microvascular complications using data mining techniques

@article{Chan2008InvestigationOD,
  title={Investigation of diabetic microvascular complications using data mining techniques},
  author={Chien-Lung Chan and Yu-Chen Liu and Shih-Hui Luo},
  journal={2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)},
  year={2008},
  pages={830-834}
}
This study theoretically analyzes and numerically explores the relationship between the physiological data and three diabetic microvascular complications: diabetic retinopathy, diabetic nephropathy, and diabetic neuropathy (foot problem). Method: The analysis results of 8,736 diabetic patients in northern Taiwan by using two data mining models: C5.0 and neural network were presented and compared. Results: It is found that Creatinine is the most important predictor for diabetic retinopathy. If… CONTINUE READING