Correction to: Scientific Reports, https://doi.org/10.1038/s41598-024-60637-y, published on 29 April 2024.
The original version of this Article contained an error.
In the section ‘Related works’,
"Alballa and Al-Turaiki20 address monetary policy concerning money laundering methods in COVID-19, focusing on diagnosis and predicting severity and mortality risk using machine learning algorithms.”
now reads:
"Alballa and Al-Turaiki20 focused on COVID-19 diagnosis and predicting severity and mortality risk using machine learning algorithms."
The original article has been corrected.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Yakovyna, V., Shakhovska, N. & Szpakowska, A. Author Correction: A novel hybrid supervised and unsupervised hierarchical ensemble for COVID-19 cases and mortality prediction. Sci Rep 14, 15720 (2024). https://doi.org/10.1038/s41598-024-66722-6
Published:
Version of record:
DOI: https://doi.org/10.1038/s41598-024-66722-6