Population-level predictive variation in machine learning diagnosis of symptomatic bacterial vaginosis
Abstract Bacterial vaginosis (BV) is a prevalent vaginal syndrome, affecting millions of women globally. The complexity of the vaginal microbiome can challenge conventional diagnostic approaches, particularly for populations of women with healthy, yet diverse vaginal microbiomes. Advanced sequencing...
Saved in:
| Main Authors: | Diandra P. Ojo, Cameron Celeste, Dion Ming, Ruogu Fang, Ivana K. Parker |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | npj Women's Health |
| Online Access: | https://doi.org/10.1038/s44294-025-00092-w |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hallmarks of Bacterial Vaginosis
by: Diana Cristina Pérez-Ibave, et al.
Published: (2025-04-01) -
Diagnosis of bacterial vaginosis: Comparison of Nugent´s and novel microscopic method
by: Nenadić Dane, et al.
Published: (2022-01-01) -
BIOFILM FORMATION AT THE BACTERIAL VAGINOSIS
by: E. S. Berezovskaya, et al.
Published: (2016-05-01) -
CONCEPTS ON ASYMPTOMATIC BACTERIAL VAGINOSIS
by: K. Telbiyska, et al.
Published: (2024-09-01) -
The Human Vaginal Bacterial Biota and Bacterial Vaginosis
by: Sujatha Srinivasan, et al.
Published: (2008-01-01)