Ensemble model for predicting chronic non-communicable diseases using Latin square extraction and fuzzy-artificial neural networks from 2013 to 2019

BACKGROUND: The presented study tracks the increase or decrease in the prevalence of seventeen different chronic non-communicable diseases in Serbia. This analysis considers factors such as region, age, and gender and is based on data from two national cross-sectional studies conducted in 2013 and 2...

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Detalles Bibliográficos
Autores principales: Rankovic, Nevena, Rankovic, Dragica, Lukic, Igor, Savic, Nikola, Jovanovic, Verica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10687296/
https://www.ncbi.nlm.nih.gov/pubmed/38034797
http://dx.doi.org/10.1016/j.heliyon.2023.e22561

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10687296/
https://www.ncbi.nlm.nih.gov/pubmed/38034797
http://dx.doi.org/10.1016/j.heliyon.2023.e22561

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