Incorporating High-Frequency Physiologic Data Using Computational Dictionary Learning Improves Prediction of Delayed Cerebral Ischemia Compared to Existing Methods

PURPOSE: Accurate prediction of delayed cerebral ischemia (DCI) after subarachnoid hemorrhage (SAH) can be critical for planning interventions to prevent poor neurological outcome. This paper presents a model using convolution dictionary learning to extract features from physiological data available...

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Detalles Bibliográficos
Autores principales: Megjhani, Murad, Terilli, Kalijah, Frey, Hans-Peter, Velazquez, Angela G., Doyle, Kevin William, Connolly, Edward Sander, Roh, David Jinou, Agarwal, Sachin, Claassen, Jan, Elhadad, Noemie, Park, Soojin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5845900/
https://www.ncbi.nlm.nih.gov/pubmed/29563892
http://dx.doi.org/10.3389/fneur.2018.00122

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5845900/
https://www.ncbi.nlm.nih.gov/pubmed/29563892
http://dx.doi.org/10.3389/fneur.2018.00122

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