Predicting outcomes in patients with aortic stenosis using machine learning: the Aortic Stenosis Risk (ASteRisk) score

OBJECTIVE: To use echocardiographic and clinical features to develop an explainable clinical risk prediction model in patients with aortic stenosis (AS), including those with low-gradient AS (LGAS), using machine learning (ML). METHODS: In 1130 patients with moderate or severe AS, we used bootstrap...

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Detalles Bibliográficos
Autores principales: Namasivayam, Mayooran, Myers, Paul D, Guttag, John V, Capoulade, Romain, Pibarot, Philippe, Picard, Michael H, Hung, Judy, Stultz, Collin M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Valvular Heart Disease
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9157386/
https://www.ncbi.nlm.nih.gov/pubmed/35641101
http://dx.doi.org/10.1136/openhrt-2022-001990

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9157386/
https://www.ncbi.nlm.nih.gov/pubmed/35641101
http://dx.doi.org/10.1136/openhrt-2022-001990

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