title: [Application of artificial neural network model to predict the health risk of dyslipidemia in individuals].
abstract: OBJECTIVE
  To establish models to predict the risk of dyslipidemia in individuals, and then to explore and evaluate new prediction models.
  
  
  METHODS
  The epidemiological survey data of 8914 community residents was selected and divided into a trained group (6686 cases) and a test group (2228 cases). Artificial neural network (ANN) and Logistic regression analysis were used to establish prediction models, and then the results were evaluated by receiver operating characteristic (ROC) curve.
  
  
  RESULTS
  The specificity (64.79%) of AAN model forecasting the results of test group was lower, but the sensitivity (94.86%), Youden's index (59.65%) and consistency rate (81.23%) of AAN model was higher than the Logistic regression predicted model (specificity = 77.49%, sensitivity = 53.51%, Youden' s index = 31.00% and consistency rate = 81.23%, respectively). Moreover, the area under ROC curve of ANN prediction model (Az = 0.824 +/- 0.009) was significantly bigger than the Logistic regression prediction model (Az = 0. 655 +/- 0.012).
  
  
  CONCLUSIONS
  The discrimination performance of ANN model is better than Logistic regression in the prediction of health risk of dyslipidemia in individuals.
authors: Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou 450001, China. tjwcj2008@zzu.edu.cn
authors: Chongjian
authors: C
authors: Wang
authors: Yuqian
authors: Y
authors: Li
authors: Dongsheng
authors: D
authors: Hu
authors: Weidong
authors: W
authors: Zhang
authors: Shaowei
authors: S
authors: Yang
authors: Yuanlin
authors: Y
authors: Xi
authors: Yuan
authors: Y
authors: Xue
authors: Wenjie
authors: W
authors: Li
mesh_terms: D000328:Adult; D000368:Aged; D002681:China / Q000453:epidemiology; D050171:Dyslipidemias / Q000453:epidemiology*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D012372:ROC Curve; D012307:Risk Factors; D012494:Sampling Studies; D011795:Surveys and Questionnaires