The Utility of Artificial Neural Networks for the Non-Invasive Prediction of Metabolic Syndrome Based on Personal Characteristics

This study investigated the diagnostic accuracy of using an artificial neural network (ANN) for the prediction of metabolic syndrome (MetS) based on socioeconomic status and lifestyle factors. The data of 27,415 subjects who went through examinations and answered questionnaires during three stages f...

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Detalles Bibliográficos
Autores principales: Wang, Feng-Hsu, Lin, Chih-Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763080/
https://www.ncbi.nlm.nih.gov/pubmed/33322521
http://dx.doi.org/10.3390/ijerph17249288

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7763080/
https://www.ncbi.nlm.nih.gov/pubmed/33322521
http://dx.doi.org/10.3390/ijerph17249288

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