Cargando…
Multimodal MRI-Based Whole-Brain Assessment in Patients In Anoxoischemic Coma by Using 3D Convolutional Neural Networks
BACKGROUND: There is an unfulfilled need to find the best way to automatically capture, analyze, organize, and merge structural and functional brain magnetic resonance imaging (MRI) data to ultimately extract relevant signals that can assist the medical decision process at the bedside of patients in...
Autores principales: | Mattia, Giulia Maria, Sarton, Benjamine, Villain, Edouard, Vinour, Helene, Ferre, Fabrice, Buffieres, William, Le Lann, Marie-Veronique, Franceries, Xavier, Peran, Patrice, Silva, Stein |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343298/ https://www.ncbi.nlm.nih.gov/pubmed/35876960 http://dx.doi.org/10.1007/s12028-022-01525-z |
Ejemplares similares
-
Outcome Prediction of Postanoxic Coma: A Comparison of Automated Electroencephalography Analysis Methods
por: Pham, Stanley D. T., et al.
Publicado: (2022) -
Self-processing in coma, unresponsive wakefulness syndrome and minimally conscious state
por: Ferré, Fabrice, et al.
Publicado: (2023) -
Modern Learning from Big Data in Critical Care: Primum Non Nocere
por: Gravesteijn, Benjamin Y., et al.
Publicado: (2022) -
Demystifying the Black Box: The Importance of Interpretability of Predictive Models in Neurocritical Care
por: Moss, Laura, et al.
Publicado: (2022) -
Blood Pressure Variability Indices for Outcome Prediction After Thrombectomy in Stroke by Using High-Resolution Data
por: Inauen, Corinne, et al.
Publicado: (2022)