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Random Forest identifies key species in differentiating between the microbiome of patients with breast cancer and healthy controls. The random forest machine learning algorithm was utilized to see if the fecal microbiome could differentiate between BC and HC. We utilized a bootstrapped random forest algorithm of 500 trees. Significance was based on the Boruta algorithm with a significance level of 0.01 highlighted in green.
