2660. Evaluating Risk for Bacterial Vaginosis Utilizing an Unsupervised Machine Learning Approach

BACKGROUND: Clustering methods using machine learning may be useful for identifying variables predicting clinical outcomes. Despite the need to better understand risk behaviors of Bacterial Vaginosis (BV), the most common cause of abnormal vaginal discharge linked to STI and HIV acquisition, machine...

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Detalles Bibliográficos
Autores principales: Rodriguez, Violeta, Pan, Yue, Salazar, Ana, Fonseca, Nicholas, Raccamarich, Patricia, Klatt, Nichole R, Weiss, Deborah Jones, Alcaide, Maria L L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Abstract
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10677155/
http://dx.doi.org/10.1093/ofid/ofad500.2271

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10677155/
http://dx.doi.org/10.1093/ofid/ofad500.2271

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