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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...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2023
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| Materias: | |
| 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 |