[The application of artificial neural network in studying landless farmer's mental health problems].
To introduce a method of classification with high precision--the artificial neural network (ANN), and to compare the results using logistic regression method. Using data from 1070 landless peasants' mental health survey, the artificial neural network models and logistic regression model were built and compared on their advantages and disadvantages of the two models. The prediction accuracy for artificial neural network was 94.229% and for logistic regression it was 51.028%. ANN appeared to have had good ability on generalization. ANN displayed advantages when conditions of classical statistical techniques could not be met or the predictive effect appeared to be unsatisfactory. Hence, ANN would make a better fracture of its application in medical research.
Zhang
Xun-bao
XB
Department of Medical Statistics and Epidemiology, School of Public Health, Xuzhou Medical College, Xuzhou 221002, China.
Huang
Shui-ping
SP
Zhuo
Lang
L
Wu
Xiu-juan
XJ
Sun
Gui-xiang
GX
Zhao
Hua-shuo
HS
Li
Lei
L
D006801:Humans; D016015:Logistic Models; D008603:Mental Health; D016571:Neural Networks, Computer; D011581:Psychological Tests / Q000706:statistics & numerical data*; D012424:Rural Population; D012959:Socioeconomic Factors