Cardiac Failure Forecasting Based on Clinical Data Using a Lightweight Machine Learning Metamodel

Accurate prediction of heart failure can help prevent life-threatening situations. Several factors contribute to the risk of heart failure, including underlying heart diseases such as coronary artery disease or heart attack, diabetes, hypertension, obesity, certain medications, and lifestyle habits...

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Detalles Bibliográficos
Autores principales: Mahmud, Istiak, Kabir, Md Mohsin, Mridha, M. F., Alfarhood, Sultan, Safran, Mejdl, Che, Dunren
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10417090/
https://www.ncbi.nlm.nih.gov/pubmed/37568902
http://dx.doi.org/10.3390/diagnostics13152540

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10417090/
https://www.ncbi.nlm.nih.gov/pubmed/37568902
http://dx.doi.org/10.3390/diagnostics13152540

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