RETRACTED: PSCNN: PatchShuffle Convolutional Neural Network for COVID-19 Explainable Diagnosis

Wang, Shui-Hua; Zhu, Ziquan; Zhang, Yu-Dong

doi:10.3389/fpubh.2021.768278

ORIGINAL RESEARCH article

Front. Public Health , 29 October 2021

Sec. Digital Public Health

Volume 9 - 2021 | https://doi.org/10.3389/fpubh.2021.768278

This article is part of the Research Topic Advanced Deep Learning Methods for Biomedical Information Analysis (ADLMBIA) View all 11 articles

RETRACTED: PSCNN: PatchShuffle Convolutional Neural Network for COVID-19 Explainable Diagnosis

Retracted

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Retraction: PSCNN: PatchShuffle convolutional neural network for COVID-19 explainable diagnosis
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$\nShui-Hua Wang&#x;$ Shui-Hua Wang¹^†

Ziquan Zhu²^†

Yu-Dong Zhang¹^*

¹School of Computing and Mathematical Sciences, University of Leicester, Leicester, United Kingdom
²Science in Civil Engineering, University of Florida, Gainesville, FL, United States

This article has been retracted. Please follow the link to the full retraction notice for details.

Citation: Wang S-H, Zhu Z and Zhang Y-D (2021) PSCNN: PatchShuffle Convolutional Neural Network for COVID-19 Explainable Diagnosis. Front. Public Health 9:768278. doi: 10.3389/fpubh.2021.768278

Received: 31 August 2021; Accepted: 29 September 2021;
Published: 29 October 2021; Retracted: 03 January 2024.

Edited by:

Shuai Li, Swansea University, United Kingdom

Reviewed by:

D Lv, Nanjing Medical University, China
Mackenzie S. Brown, Edith Cowan University, Australia

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RETRACTED: PSCNN: PatchShuffle Convolutional Neural Network for COVID-19 Explainable Diagnosis

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