Whole-genome sequencing and machine learning reveal key drivers of delayed sputum conversion in rifampicin-resistant tuberculosis

Whole-genome sequencing and machine learning reveal key drivers of delayed sputum conversion in rifampicin-resistant tuberculosis

Rifampicin-resistant tuberculosis (RR-TB) remains a major global health challenge, with delayed sputum culture conversion (SCC) predicting poor treatment outcomes. This study integrated whole-genome sequencing (WGS) and machine learning to identify clinical and genomic determinants of SCC failure in...

Full description

Saved in:
Bibliographic Details
Main Authors: Qing Fang, Xiangchen Li, Yewei Lu, Junshun Gao, Yvette Wu, Yi Chen, Yang Che
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Cellular and Infection Microbiology
Subjects:
rifampicin-resistant tuberculosis
whole-genome sequencing
sputum culture conversion
machine learning
drug resistance mutations
Online Access:https://www.frontiersin.org/articles/10.3389/fcimb.2025.1641385/full
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items