Cargando…
Minimal Patient Clinical Variables to Accurately Predict Stress Echocardiography Outcome: Validation Study Using Machine Learning Techniques
BACKGROUND: Stress echocardiography is a well-established diagnostic tool for suspected coronary artery disease (CAD). Cardiovascular risk factors are used in the assessment of the probability of CAD. The link between the outcome of stress echocardiography and patients’ variables including risk fact...
Autores principales: | Bennasar, Mohamed, Banks, Duncan, Price, Blaine A, Kardos, Attila |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7293061/ https://www.ncbi.nlm.nih.gov/pubmed/32469316 http://dx.doi.org/10.2196/16975 |
Ejemplares similares
-
Multiparametric Stress Echocardiography in the Diagnosis of IOCA and INOCA: Role of CFVR Measurement
por: Kardos, Attila, et al.
Publicado: (2023) -
‘How to do’: digital-interactive-interpretation course for stress echocardiography
por: Kardos, Attila, et al.
Publicado: (2021) -
Development and validation of echocardiography-based machine-learning models to predict mortality
por: Valsaraj, Akshay, et al.
Publicado: (2023) -
Accurate contact predictions using covariation techniques and machine learning
por: Kosciolek, Tomasz, et al.
Publicado: (2015) -
Is Demography Destiny? Application of Machine Learning Techniques to Accurately Predict Population Health Outcomes from a Minimal Demographic Dataset
por: Luo, Wei, et al.
Publicado: (2015)