A machine-learning based model for automated recommendation of individualized treatment of rifampicin-resistant tuberculosis.

Lennert Verboven Steven Callens John M BlackGary MaartensKelly E DooleySamantha PotgieterRuben Cartuyvelsnull nullKris LaukensRobin M WarrenAnnelies Van Rie

Published in: PloS one (2024)

Our findings suggest that global implementation of the novel treatment recommender CDSS holds the potential to improve treatment outcomes of patients with RR-TB, especially those with 'difficult-to-treat' forms of RR-TB.

Keyphrases

mycobacterium tuberculosis
machine learning
healthcare
primary care
pulmonary tuberculosis
combination therapy
artificial intelligence
risk assessment
single cell
adverse drug
hiv infected
drug induced