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

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

doi:10.1371/journal.pone.0176771

Abstract

[This corrects the article DOI: 10.1371/journal.pone.0070571.].

Highlights

Prior to publication of this PLOS ONE article [1], the authors published closely related work at BMC Medical Informatics and Decision Making, in a publication titled "Artificial neural network models for prediction of cardiovascular autonomic dysfunction in general Chinese population" [2]
The authors have explained that the BMC Medical Informatics and Decision Making article described work on models based on artificial neural network for the prediction of cardiovascular autonomic dysfunction, while the PLOS ONE article reports the comparison between artificial neural network and linear regression models in the same Chinese sample
In the PLOS ONE article, reused text comprises the majority of the Introduction, all Methods subsections except “Multivariate logistic regression models,” and the following text in the Results and Discussion sections: Results

Summary

Introduction

Prior to publication of this PLOS ONE article [1], the authors published closely related work at BMC Medical Informatics and Decision Making, in a publication titled "Artificial neural network models for prediction of cardiovascular autonomic dysfunction in general Chinese population" [2]. The journal office has been alerted to concerns regarding the extent of overlap between these two articles. The authors have explained that the BMC Medical Informatics and Decision Making article described work on models based on artificial neural network for the prediction of cardiovascular autonomic dysfunction, while the PLOS ONE article reports the comparison between artificial neural network and linear regression models in the same Chinese sample.

Results

Conclusion