The purpose of this study was to select markers that improve predictive power through machine learning among various vaginal microbiota and develop an excellent prediction algorithm that combines clin
We conducted a systematic review of the Medline database (U.S. National Library of Medicine, National Institutes of Health, Bethesda, MD, U.S.A) to determine if consistent molecular vaginal microbiota