Using unsupervised machine learning to classify behavioral risk markers of bacterial vaginosis.

Machine learning methods may be particularly useful in identifying specific clusters of high-risk behaviors, in developing interventions intended to reduce BV and IVP, and ultimately in reducing the risk of HIV infection among women.