Evaluating machine learning-powered classification algorithms which utilize variants in the GCKR gene to predict metabolic syndrome: Tehran Cardio-metabolic Genetics Study

BACKGROUND: Metabolic syndrome (MetS) is a prevalent multifactorial disorder that can increase the risk of developing diabetes, cardiovascular diseases, and cancer. We aimed to compare different machine learning classification methods in predicting metabolic syndrome status as well as identifying in...

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Detalles Bibliográficos
Autores principales: Akbarzadeh, Mahdi, Alipour, Nadia, Moheimani, Hamed, Zahedi, Asieh Sadat, Hosseini-Esfahani, Firoozeh, Lanjanian, Hossein, Azizi, Fereidoun, Daneshpour, Maryam S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8994379/
https://www.ncbi.nlm.nih.gov/pubmed/35397593
http://dx.doi.org/10.1186/s12967-022-03349-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8994379/
https://www.ncbi.nlm.nih.gov/pubmed/35397593
http://dx.doi.org/10.1186/s12967-022-03349-z

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