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CORRECTION article

Front. Aging Neurosci., 17 July 2018
Sec. Alzheimer's Disease and Related Dementias

Corrigendum: Novel Prehospital Prediction Model of Large Vessel Occlusion Using Artificial Neural Network

  • 1Department of Neurology, The Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China
  • 2Department of Engineering, Microcloud Communication Technology, Hangzhou, China

A corrigendum on
Novel Prehospital Prediction Model of Large Vessel Occlusion Using Artificial Neural Network

by Chen, Z., Zhang, R., Xu, F., Gong, X., Shi, F., Zhang, M., et al. (2018). Front. Aging Neurosci. 10:181. doi: 10.3389/fnagi.2018.00181

There is an error in the Funding statement. The correct number for the Science Technology Department of Zhejiang Province is 2018C04011. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way.

The original article has been updated.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Keywords: large vessel occlusion, artificial neural network, stroke, scale, NIHSS

Citation: Chen Z, Zhang R, Xu F, Gong X, Shi F, Zhang M and Lou M (2018) Corrigendum: Novel Prehospital Prediction Model of Large Vessel Occlusion Using Artificial Neural Network. Front. Aging Neurosci. 10:222. doi: 10.3389/fnagi.2018.00222

Received: 27 June 2018; Accepted: 28 June 2018;
Published: 17 July 2018.

Approved by:

Frontiers In Aging Neuroscience Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2018 Chen, Zhang, Xu, Gong, Shi, Zhang and Lou. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Min Lou, lm99@zju.edu.cn; loumingxc@vip.sina.com

These authors have contributed equally to this work.

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.