HIGHLIGHTS
- who: Mahdi Akbarzadeh from the Shahid Beheshti University of Medical, Tehran, Iran have published the research work: Evaluating machine learning-powered classification algorithms which utilize variants in the GCKR gene to predict metabolic syndrome: Tehran Cardio-metabolic Genetics Study, in the Journal: (JOURNAL)
- what: The authors aimed to compare different machine learning classification methods in predicting metabolic syndrome status as well as identifying influential genetic or environmental risk factors. The authors aimed to compare certain machine_learning models (decision tree, Random Forest, support vector machines) with traditional statistical models (logistic regression, linear and quadratic discriminant analysis . . .
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