Cargando…
Diagnostic and prognostic EEG analysis of critically ill patients: A deep learning study
Visual interpretation of electroencephalography (EEG) is time consuming, may lack objectivity, and is restricted to features detectable by a human. Computer-based approaches, especially deep learning, could potentially overcome these limitations. However, most deep learning studies focus on a specif...
Autores principales: | Jonas, Stefan, Müller, Michael, Rossetti, Andrea O., Rüegg, Stephan, Alvarez, Vincent, Schindler, Kaspar, Zubler, Frédéric |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9441331/ https://www.ncbi.nlm.nih.gov/pubmed/36049354 http://dx.doi.org/10.1016/j.nicl.2022.103167 |
Ejemplares similares
-
EEG spindles integrity in critical care adults. Analysis of a randomized trial
por: Vassallo, Paola, et al.
Publicado: (2021) -
Standardized visual EEG features predict outcome in patients with acute consciousness impairment of various etiologies
por: Müller, Michael, et al.
Publicado: (2020) -
Continuous vs Routine Electroencephalogram in Critically Ill Adults With Altered Consciousness and No Recent Seizure: A Multicenter Randomized Clinical Trial
por: Rossetti, Andrea O., et al.
Publicado: (2020) -
Continuous Versus Routine Standardized Electroencephalogram for Outcome Prediction in Critically Ill Adults: Analysis From a Randomized Trial
por: Beuchat, Isabelle, et al.
Publicado: (2021) -
Informed consent in critically ill adults participating to a randomized trial
por: Guinchard, Milène, et al.
Publicado: (2020)