Cargando…
Prediction of all-cause mortality in coronary artery disease patients with atrial fibrillation based on machine learning models
BACKGROUND: Machine learning (ML) can include more diverse and more complex variables to construct models. This study aimed to develop models based on ML methods to predict the all-cause mortality in coronary artery disease (CAD) patients with atrial fibrillation (AF). METHODS: A total of 2037 CAD p...
Autores principales: | Liu, Xinyun, Jiang, Jicheng, Wei, Lili, Xing, Wenlu, Shang, Hailong, Liu, Guangan, Liu, Feng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8520292/ https://www.ncbi.nlm.nih.gov/pubmed/34656086 http://dx.doi.org/10.1186/s12872-021-02314-w |
Ejemplares similares
-
Antithrombotic therapy in coronary artery disease patients with atrial fibrillation
por: Wei, Lili, et al.
Publicado: (2020) -
Interpretable machine learning models for early prediction of acute kidney injury after cardiac surgery
por: Jiang, Jicheng, et al.
Publicado: (2023) -
Population Trends in All‐Cause Mortality and Cause Specific–Death With Incident Atrial Fibrillation
por: Singh, Sheldon M., et al.
Publicado: (2020) -
The Association Between Recurrence of Atrial Fibrillation and Revascularization in Patients With Coronary Artery Disease After Catheter Ablation
por: Chen, Xiaowei, et al.
Publicado: (2021) -
Reduced-Dose Rivaroxaban Is Associated with Lower All-Cause Mortality in Older Patients with Nonvalvular Atrial Fibrillation
por: Chiou, Wei-Ru, et al.
Publicado: (2023)