Back to search

Article

Machine learning approaches for tuberculosis prevalence and risk factor association among high-risk groups in Kigali health facilities

2026-07-27

Abstract excerpt

<title>Abstract</title> <p>Background Tuberculosis (TB) remains a major global health challenge, disproportionately affecting vulnerable populations in resource-limited settings. In Rwanda, the burden is high among high-risk groups including prisoners, mining workers, people living with HIV, and healthcare workers. Despite well-established national surveillance infrastructure, published evidence on applying mach...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
e0230d86-4df2-540c-8d7e-da5a02eda4ba
DOI
10.21203/rs.3.rs-10453356/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Machine learning approaches for tuberculosis prevalence and risk factor association among high-risk groups in Kigali health facilitiesDOI 10.21203/rs.3.rs-10453356/v1
Select a neighboring publication to make it the new centre.