Link to the original source: https://www.sciencedirect.com/science/article/pii/S2666520424000109?via%3Dihub
APA: Garcia-Vilana, Silvia; Kumar, Vikas; Kumar, Saurav; Barberia, Eneko; Landin, Ines; Granado-Font, Ester; Sola-Munoz, Silvia; Jimenez-Fabrega, Xavier; B (2024). Study of risk factors for injuries due to cardiopulmonary resuscitation with special focus on the role of the heart: A machine learning analysis of a prospective registry with multiple sources of information (ReCaPTa Study). Resuscitation Plus, 17(), 100559-. DOI: 10.1016/j.resplu.2024.100559
Paper original source: Resuscitation Plus. 17 100559-
Article's DOI: 10.1016/j.resplu.2024.100559
Journal publication year: 2024
Entity: Universitat Rovira i Virgili
Paper version: info:eu-repo/semantics/publishedVersion
Record's date: 2024-10-12
URV's Author/s: Barberia Marcalain, Eneko / Bardají Ruiz, Alfredo / Kumar, Vikas / Landin Roig, Maria Ines
Department: Enginyeria Química
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Publication Type: Journal Publications
Author, as appears in the article.: Garcia-Vilana, Silvia; Kumar, Vikas; Kumar, Saurav; Barberia, Eneko; Landin, Ines; Granado-Font, Ester; Sola-Munoz, Silvia; Jimenez-Fabrega, Xavier; Bardaji, Alfredo; Hardig, Bjarne Madsen; Azeli, Youcef
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Thematic Areas: Cardiology and cardiovascular medicine, Critical care medicine, Emergency medicine, Emergency nursing
Author's mail: eneko.barberia@urv.cat, alfredo.bardaji@urv.cat, eneko.barberia@urv.cat, mariaines.landin@urv.cat, vikas.kumar@urv.cat