Heart disease prediction using autoencoder and DenseNet architecture

Heart disease continues to be a prominent cause of death globally, emphasizing the critical requirement for precise prediction techniques and prompt therapies. This research presents a new method that utilizes the collective capabilities of autoencoder and DenseNet architectures to predict heart ill...

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Detalles Bibliográficos

Principais autores:	Norah Saleh Alghamdi, Mohammed Zakariah, Achyut Shankar, Wattana Viriyasitavat
Formato:	Artigo
Idioma:	Inglês
Publicado:	Elsevier 2024-12-01
Series:	Egyptian Informatics Journal
Assuntos:	Heart Disease Heart Disease Cleveland dataset Machine-Learning Sparse Autoencoder DenseNet
Acceso en liña:	http://www.sciencedirect.com/science/article/pii/S1110866524001221
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