Skip to main content
Frontiers in Physiology logoLink to Frontiers in Physiology
. 2026 Oct 2;17:2009113. doi: 10.3389/fphys.2026.2009113

Correction: Machine learning for enhancing the ablation outcomes using recurrence quantification analysis in human persistent atrial fibrillation

Noor N Qaqos 1,2,*, Fernando S Schlindwein 1,3, G André Ng 3,4, Xin Li 1,3
PMCID: PMC13673446  PMID: 42890521

In the published article, there was a mistake in the Funding statement. The correct Funding statement for this article is:

“The author(s) declared that financial support was received for this work and/or its publication. This work was supported by the NIHR Leicester Biomedical Research Centre, United Kingdom. GAN and XL is supported by British Heart Foundation Research Excellence Award (RE/24/130031), Medical Research Council Biomedical Catalyst Developmental Pathway Funding Scheme (MR/S037306/1) and NIHR i4i grant (NIHR204553). GAN is also supported by British Heart Foundation Programme Grant (RG/17/3/32774). Noor N. Qaqos received a PhD scholarship from the Higher Committee for Educational Development (HCED) in Iraq. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.”

The original article has been updated.

Footnotes

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

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.


Articles from Frontiers in Physiology are provided here courtesy of Frontiers Media SA

RESOURCES