- 1Department of Computer Arquitecture and Automation, Universidad Complutense de Madrid, Madrid, Spain
- 2Servicio de Neurología, Hospital Universitario de La Princesa, IIS-Princesa – Instituto de Investigación Sanitaria Hospital Universitario de La Princesa, Madrid, Spain
- 3Stroke Commission, Madrid Emergency Medical Service (SUMMA 112), Madrid, Spain
A Correction on
Early stroke detection through machine learning in the prehospital setting
By Ríos Delgado M, Reig Roselló G, Riera- Lopez N, Vivancos JA and Ayala JL. Frontiers in Cardiovascular Medicine, 12, 2025. doi: 10.3389/fcvm.2025.1629853
An incorrect number was provided for Instituto de Salud Carlos III (ISCIII). The correct number is PI22/01454.
The original version of this article has been updated.
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Keywords: stroke, LVO, emeregency medical services, prehospital, machine learning, genetic algorithms, clinical data, hemodynamic data
Citation: Ríos Delgado M, Reig Roselló G, Riera-Lopez N, Vivancos JA and Ayala JL (2025) Correction: Early stroke detection through machine learning in the prehospital setting. Front. Cardiovasc. Med. 12:1708205. doi: 10.3389/fcvm.2025.1708205
Received: 18 September 2025; Accepted: 6 October 2025;
Published: 23 October 2025.
Approved by: Frontiers Editorial Office, Frontiers Media SA, Switzerland
Copyright: © 2025 Ríos Delgado, Reig Roselló, Riera-Lopez, Vivancos and Ayala. 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: María Ríos Delgado, bXJpb3MwOUB1Y20uZXM=
 Gemma Reig Roselló2
Gemma Reig Roselló2