title: The relationship between left ventricle myocardial performance index of healthy women and geographical factors.
abstract: The study focused on the relationship between geographical factors and left ventricular myocardial performance index (MPI)reference value, analyed the different distribution of MPI, and then provided a scientific basis for clinical examination. This study collected MPI reference values of 2545 healthy women from 91 cities in China, used the Moran's index to determin the spatial relationship, selected 25 geographical factors, examined the significance between MPI and geographical factors by correlation analysis, through the significance test, and extracted seven significant factors to build the artificial neural network (ANN) model and principal component analysis (PCA) model. Through calculating the relative error, the ANN model was chosen as the better model to predict the values. By normality test for the predicted values, the geographical distribution was made by disjunctive kriging interpolation. The predicted values decrease from north to south. If geographical factors are obtained in one location, the MPI of healthy women in this area can be predicted by the ANN model. Synthesizing the influence of physiological and geographical could be more scientific to formulate the MPI reference value.
authors: College of Tourist and Environment Science, Shaanxi Normal University, Xi'an, 710119, Shaanxi, China. hx_125@126.com.
authors: Xiao
authors: X
authors: Han
authors: College of Tourist and Environment Science, Shaanxi Normal University, Xi'an, 710119, Shaanxi, China. gemiao@snnu.edu.cn.
authors: Miao
authors: M
authors: Ge
authors: College of Tourist and Environment Science, Shaanxi Normal University, Xi'an, 710119, Shaanxi, China.
authors: Jie
authors: J
authors: Dong
authors: College of Tourist and Environment Science, Shaanxi Normal University, Xi'an, 710119, Shaanxi, China.
authors: Zixuan
authors: Z
authors: Wang
authors: College of Tourist and Environment Science, Shaanxi Normal University, Xi'an, 710119, Shaanxi, China.
authors: Jinwei
authors: J
authors: He
authors: College of Tourist and Environment Science, Shaanxi Normal University, Xi'an, 710119, Shaanxi, China.
authors: Rongrong
authors: R
authors: Yang
mesh_terms: D002681:China; D005260:Female; D005843:Geography; D006801:Humans; D016571:Neural Networks, Computer; D025341:Principal Component Analysis; D062206:Spatial Analysis; D016277:Ventricular Function, Left; D014887:Weather
keywords: Artificial neural network; Cardiac function; Disjunctive kriging; Left ventricle myocardial performance index; Principal component analysis