Retraction: Cerebral microbleed detection via convolutional neural network and extreme learning machine

, Frontiers Editorial Office

doi:10.3389/fncom.2023.1358283

RETRACTION article

Front. Comput. Neurosci., 28 December 2023

Volume 17 - 2023 | https://doi.org/10.3389/fncom.2023.1358283

Retraction: Cerebral microbleed detection via convolutional neural network and extreme learning machine

This article is a retraction of:

RETRACTED: Cerebral Microbleed Detection via Convolutional Neural Network and Extreme Learning Machine
1. Read original article

$\r\nFrontiers Editorial Office$ Frontiers Editorial Office^*

A Retraction of the Original Research Article
Cerebral microbleed detection via convolutional neural network and extreme learning machine

by Lu, S., Liu, S., Wang, S.-H., and Zhang, Y.-D. (2021). Front. Comput. Neurosci. 15:738885. doi: 10.3389/fncom.2021.738885

The journal retracts the 10 September 2021 article cited above.

Following publication, the publisher uncovered evidence that false identities were used in the peer-review process. The assignment of fake reviewers was confirmed by an investigation, conducted in accordance with Frontiers' policies and the Committee on Publication Ethics (COPE) guidelines. Given the concerns, the editors no longer have confidence in the findings presented in the article. UPDATE (30 July 2024): This notice is to alert readers of this matter, it does not imply involvement of the co-authors.

This retraction was approved by the Chief Editors of Frontiers in Computational Neuroscience and the Chief Executive Editor of Frontiers. The authors received a communication regarding the retraction and had a chance to respond. This communication has been recorded by the publisher.

Citation: Frontiers Editorial Office (2023) Retraction: Cerebral microbleed detection via convolutional neural network and extreme learning machine. Front. Comput. Neurosci. 17:1358283. doi: 10.3389/fncom.2023.1358283

Received: 19 December 2023; Accepted: 21 December 2023;
Published: 28 December 2023.

Approved by:

Si Wu, Peking University, China

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