Cargando…
Comparison of Electrocardiographic Parameters by Gender in Heart Failure Patients with Preserved Ejection Fraction via Artificial Intelligence
Background: Heart failure (HF) causes high morbidity and mortality worldwide. The prevalence of HF with preserved ejection fraction (HFpEF) is increasing compared with HF with reduced ejection fraction (HFrEF). Patients with HFpEF are a patient group with a high rate of hospitalization despite medic...
Autores principales: | Yilmaz, Rustem, Öz, Ersoy |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10605906/ https://www.ncbi.nlm.nih.gov/pubmed/37892041 http://dx.doi.org/10.3390/diagnostics13203221 |
Ejemplares similares
-
Artificial intelligence assessment for early detection of heart failure with preserved ejection fraction based on electrocardiographic features
por: Kwon, Joon-myoung, et al.
Publicado: (2020) -
Gender-related differences in heart failure with preserved ejection fraction
por: Duca, Franz, et al.
Publicado: (2018) -
Electrocardiographic Predictors of Heart Failure With Reduced Versus Preserved Ejection Fraction: The Multi‐Ethnic Study of Atherosclerosis
por: O'Neal, Wesley T., et al.
Publicado: (2017) -
Decoding empagliflozin’s molecular mechanism of action in heart failure with preserved ejection fraction using artificial intelligence
por: Bayes-Genis, Antoni, et al.
Publicado: (2021) -
Heart failure with preserved ejection fraction
por: Rigolli, Marzia, et al.
Publicado: (2013)