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

ConclusionsMachine 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.
Source: Archives of Gynecology and Obstetrics - Category: OBGYN Source Type: research