Comparison of Prediction Model for Cardiovascular Autonomic Dysfunction Using Artificial Neural Network and Logistic Regression Analysis

Zi-Hui Tang, Juanmei Liu, Fangfang Zeng, Zhongtao Li, Xiaoling Yu and Linuo Zhou

PLOS ONE, 2013, vol. 8, issue 8, 1-8

Abstract: Background: This study aimed to develop the artificial neural network (ANN) and multivariable logistic regression (LR) analyses for prediction modeling of cardiovascular autonomic (CA) dysfunction in the general population, and compare the prediction models using the two approaches. Methods and Materials: We analyzed a previous dataset based on a Chinese population sample consisting of 2,092 individuals aged 30–80 years. The prediction models were derived from an exploratory set using ANN and LR analysis, and were tested in the validation set. Performances of these prediction models were then compared. Results: Univariate analysis indicated that 14 risk factors showed statistically significant association with the prevalence of CA dysfunction (P

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0070571

DOI: 10.1371/journal.pone.0070571

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