Synthetic Data Generation for Pediatric Diabetes Research Using GANs and WGANs.

Pediatric diabetes research is often constrained by data scarcity, hindering the development of accurate predictive models for clinical applications. This study addresses this limitation by evaluating the effectiveness of Generative Adversarial Networks (GANs) and Wasserstein GANs (WGANs) in generat...

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Publicado en:	Revista Mexicana de Ingeniería Biomédica Vol. 46; no. 1; pp. 1 - 29
Autores principales:	García-Domínguez, Antonio, Galván-Tejada, Carlos E., Magallanes-Quintanar, Rafael, Cruz-López, Miguel, Alexander Vázquez-Moreno, Miguel, Acosta-Cruz, Erika
Formato:	Artículo
Publicado:	Sociedad Mexicana de Ingenieria Biomedica, A.C. Jan-Apr2025
Materias:	Generative adversarial networks Diabetes in children Synthetic data Prediction models Data quality Clinical medicine
Acceso en línea:	Ver este registro en EBSCOhost