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Regularized Machine Learning Models for Prediction of Metabolic Syndrome Using GCKR, APOA5, and BUD13 Gene Variants: Tehran Cardiometabolic Genetic Study
OBJECTIVE: Metabolic syndrome (MetS) is a complex multifactorial disorder that considerably burdens healthcare systems. We aim to classify MetS using regularized machine learning models in the presence of the risk variants of GCKR, BUD13 and APOA5, and environmental risk factors. MATERIALS AND METHO...
Autores principales: | Alipour, Nadia, Kazemnejad, Anoshirvan, Akbarzadeh, Mahdi, Eskandari, Farzad, Zahedi, Asiyeh Sadat, Daneshpour, Maryam S |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Royan Institute
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10542204/ https://www.ncbi.nlm.nih.gov/pubmed/37641415 http://dx.doi.org/10.22074/CELLJ.2023.2000864.1294 |
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