Artificial intelligence assessment for early detection of heart failure with preserved ejection fraction based on electrocardiographic features

AIMS: Although heart failure with preserved ejection fraction (HFpEF) is a rapidly emerging global health problem, an adequate tool to screen it reliably and economically does not exist. We developed an interpretable deep learning model (DLM) using electrocardiography (ECG) and validated its perform...

Descripción completa

Detalles Bibliográficos
Autores principales: Kwon, Joon-myoung, Kim, Kyung-Hee, Eisen, Howard J, Cho, Younghoon, Jeon, Ki-Hyun, Lee, Soo Youn, Park, Jinsik, Oh, Byung-Hee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707919/
https://www.ncbi.nlm.nih.gov/pubmed/36711179
http://dx.doi.org/10.1093/ehjdh/ztaa015

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707919/
https://www.ncbi.nlm.nih.gov/pubmed/36711179
http://dx.doi.org/10.1093/ehjdh/ztaa015

Ejemplares similares