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CORRECTION article

Front. Aging Neurosci., 17 March 2022
Sec. Alzheimer's Disease and Related Dementias
Volume 14 - 2022 | https://doi.org/10.3389/fnagi.2022.879453

Corrigendum: A 5-min Cognitive Task With Deep Learning Accurately Detects Early Alzheimer's Disease

This article is a correction to:

  1. A 5-min Cognitive Task With Deep Learning Accurately Detects Early Alzheimer's Disease

    1. Read original article
\nIbrahim Almubark, Ibrahim Almubark1,2*Lin-Ching ChangLin-Ching Chang1Kyle F. ShattuckKyle F. Shattuck3Thanh NguyenThanh Nguyen1Raymond Scott TurnerRaymond Scott Turner4Xiong Jiang Xiong Jiang3*
  • 1Department of Electrical Engineering and Computer Science, Catholic University of America, Washington, DC, United States
  • 2Department of Information Technology, College of Computer, Qassim University, Buraydah, Saudi Arabia
  • 3Department of Neuroscience, Georgetown University Medical Center, Washington, DC, United States
  • 4Department of Neurology, Georgetown University Medical Center, Washington, DC, United States

A Corrigendum on
A 5-min Cognitive Task With Deep Learning Accurately Detects Early Alzheimer's Disease

by Almubark, I., Chang, L-C., Shattuck, K. F., Nguyen, T., Turner, R. S., and Jiang, X. (2020). Front. Aging Neurosci. 12:603179. doi: 10.3389/fnagi.2020.603179

In the original article, we neglected to include the funders “Qassim University and the Deanship of Scientific Research to Ibrahim Almubark.” The Funding Statement has been updated to include “The authors would also like to thank Qassim University and the Deanship of Scientific Research for their support and funding the publication.”

In the published article, there was an error regarding the affiliations for “Ibrahim Almubark.” As well as having affiliation 1, they should also have affiliation 2.

The authors apologize for these errors and state that they do not change the scientific conclusions of the article in any way. The original article has been updated.

Publisher's Note

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.

Keywords: Alzheimer's disease, machine learning, artificial neural networks, inhibition of return, neuropsychological test

Citation: Almubark I, Chang L-C, Shattuck KF, Nguyen T, Turner RS and Jiang X (2022) Corrigendum: A 5-min Cognitive Task With Deep Learning Accurately Detects Early Alzheimer's Disease. Front. Aging Neurosci. 14:879453. doi: 10.3389/fnagi.2022.879453

Received: 19 February 2022; Accepted: 21 February 2022;
Published: 17 March 2022.

Approved by: Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2022 Almubark, Chang, Shattuck, Nguyen, Turner and Jiang. 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: Ibrahim Almubark, 47almubark@cua.edu; Xiong Jiang, Xiong.Jiang@georgetown.edu

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.