A hybrid stacking ensemble approach combining fuzzy logistic regression and fuzzy neural networks for enhanced COVID-19 diagnostic accuracy

Abstract The timely and accurate diagnosis of COVID-19 remains crucial to managing the pandemic and preventing further transmission. Traditional diagnostic models often struggle with the complexity and uncertainty inherent in medical data related to COVID-19. This study proposes a novel hybrid stack...

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Autores principales: Masoumeh Habibi Ganjgah, Parvin Azhdari, Kianoush Fathi Vajargah
Formato: Artigo
Lenguaje:Inglês
Publicado: Springer 2025-09-01
Colección:Discover Applied Sciences
Materias:
Hybrid stacking ensemble
Fuzzy logistic regression (FLR)
Fuzzy artificial neural networks (FANNs)
COVID-19 diagnosis
Z-numbers
Uncertainty modeling
Acceso en línea:https://doi.org/10.1007/s42452-025-07456-6
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