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