Cargando…
Aortic Distensibility Measured by Automated Analysis of Magnetic Resonance Imaging Predicts Adverse Cardiovascular Events in UK Biobank
BACKGROUND: Automated analysis of cardiovascular magnetic resonance images provides the potential to assess aortic distensibility in large populations. The aim of this study was to compare the prediction of cardiovascular events by automated cardiovascular magnetic resonance with those of other simp...
Autores principales: | Cecelja, Marina, Ruijsink, Bram, Puyol‐Antón, Esther, Li, Ye, Godwin, Harriet, King, Andrew P., Razavi, Reza, Chowienczyk, Phil |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9851433/ https://www.ncbi.nlm.nih.gov/pubmed/36444831 http://dx.doi.org/10.1161/JAHA.122.026361 |
Ejemplares similares
-
Deep Learning for Classification and Selection of Cine CMR Images to Achieve Fully Automated Quality-Controlled CMR Analysis From Scanner to Report
por: Vergani, Vittoria, et al.
Publicado: (2021) -
Fairness in Cardiac Magnetic Resonance Imaging: Assessing Sex and Racial Bias in Deep Learning-Based Segmentation
por: Puyol-Antón, Esther, et al.
Publicado: (2022) -
Fully Automated, Quality-Controlled Cardiac Analysis From CMR: Validation and Large-Scale Application to Characterize Cardiac Function
por: Ruijsink, Bram, et al.
Publicado: (2019) -
Automated quantification of myocardial tissue characteristics from native T(1) mapping using neural networks with uncertainty-based quality-control
por: Puyol-Antón, Esther, et al.
Publicado: (2020) -
The Role of AI in Characterizing the DCM Phenotype
por: Asher, Clint, et al.
Publicado: (2021)