Predicting defibrillation success in out-of-hospital cardiac arrested patients: Moving beyond feature design.

Ivanovic, Marija D; Hannink, Julius; Ring, Matthias; Baronio, Fabio; Vukcevic, Vladan; Hadzievski, Ljupco; Eskofier, Bjoern

Ivanovic, Marija D; Hannink, Julius; Ring, Matthias; Baronio, Fabio; Vukcevic, Vladan; Hadzievski, Ljupco; Eskofier, Bjoern.

Afiliación

Ivanovic MD; Vinca Institute of Nuclear Scientists, University of Belgrade, Belgrade, Serbia. Electronic address: marijap@vin.bg.ac.rs.
Hannink J; Machine Learning and Data Analytics Lab, Department of Computer Science, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany.
Ring M; Machine Learning and Data Analytics Lab, Department of Computer Science, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany.
Baronio F; CNR and Department of Information Engineering, University of Brescia, Brescia, Italy.
Vukcevic V; School of Medicine, University of Belgrade, Belgrade, Serbia.
Hadzievski L; Vinca Institute of Nuclear Scientists, University of Belgrade, Belgrade, Serbia; Diasens, Belgrade, Serbia.
Eskofier B; Machine Learning and Data Analytics Lab, Department of Computer Science, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany.

Artif Intell Med ; 110: 101963, 2020 11.

Article en En | MEDLINE | ID: mdl-33250144

Asunto(s)

Aprendizaje Automático; Redes Neurales de la Computación; Hospitales; Humanos; Estudios Prospectivos

Palabras clave

Convolutional neural networks (CNN); Deep learning; Defibrillation; Shock outcome; Ventricular fibrillation (VF)

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Redes Neurales de la Computación / Aprendizaje Automático Tipo de estudio: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Artif Intell Med Asunto de la revista: INFORMATICA MEDICA Año: 2020 Tipo del documento: Article Pais de publicación: Países Bajos

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