Application of Data Mining Technology in Risk Prediction Model for Lung Cancer
10.3971/j.issn.1000-8578.2021.20.0829
- VernacularTitle:数据挖掘技术在肺癌危险度预测模型中的应用
- Author:
Zibo GAO
1
;
Di LI
;
Shuyin DUAN
;
Xiaolei ZHOU
;
Hong LIU
;
Jing WANG
;
Wei WANG
;
Yongjun WU
Author Information
1. College of Public Health, Zhengzhou University, Zhengzhou 450001, China
- Publication Type:Research Article
- Keywords:
Lung neoplasms;
Decision trees C5.0;
Artificial neural network;
Risk prediction
- From:
Cancer Research on Prevention and Treatment
2021;48(5):479-483
- CountryChina
- Language:Chinese
-
Abstract:
Objective To establish a lung cancer risk prediction model using data mining technology and compare the performance of decision tree C5.0 and artificial neural networks in the application of risk prediction model, and to explore the value of data mining techniques in lung cancer risk prediction. Methods We collected the data of 180 patients with lung cancer and 240 patients with benign lung lesion which contained 17 variables of risk factors and clinical symptoms. Decision tree C5.0 and artificial neural networks models were established to compare the prediction performance. Results There were 420 valid samples collected in total and proportioned with the ratio of 7:3 for the training set and testing set. The accuracy, sensitivity, specificity, Youden index, positive predictive value, negative predictive value and AUC of artificial neural networks model were 65.3%, 61.7%, 73.3%, 0.350, 54.9%, 73.1% and 0.675 (95%CI: 0.628-0.720) in testing set; those of decision tree C5.0 model were 61.0%, 47.8%, 80.4%, 0.282, 35.3%, 80.6% and 0.641 (95%CI: 0.593-0.687) in testing set. Conclusion The artificial neural networks model is superior to the decision tree C5.0 model at overall performance and it has potential application value in the risk prediction of lung cancer.
