Background#R##N#Bacterial vaginosis (BV) is a disease associated with the vagina microbiome. It is highly prevalent and is characterized by symptoms including odor, discharge and irritation. No single microbe has been found to cause BV. In this paper we use random forests and logistic regression classifiers to model the relationship between the microbial community and BV. We use subsets of the microbial community features in order to determine which features are important to the classification models.
['Daniel Beck', 'James A. Foster']
Machine learning classifiers provide insight into the relationship between microbial communities and bacterial vaginosis