Watch: AI and blood test could change the way TB is diagnosed
A new international research project called AddiCAD is combining AI-driven chest X-ray analysis with blood-based biomarker testing to improve tuberculosis diagnosis. The goal is to create a faster, more accurate, and less invasive diagnostic tool for global health use.
Why it matters
Improving TB detection is critical for global health, as millions of cases remain undiagnosed due to current diagnostic limitations.
A new international research project aims to make TB testing quicker and easier for patients by combining AI technology with a simple finger-prick blood test.
The project, co-ordinated by Stellenbosch University (SU), will develop and test a new way of detecting TB that could reduce the need for patients to provide sputum samples (mucus coughed up from the lungs).
If successful, the technology could help healthcare workers identify TB faster, allowing patients to start treatment sooner and reducing the risk of the disease spreading.
One of the major challenges in the fight against the disease is effective detection. Of the estimated 10.7 million new cases of TB each year, around 2.5 million people remain undiagnosed. This is partly because current diagnostic tools are often too expensive, laboratory-dependent or difficult to deploy at the point of care.
Get smarter about the news
Sign up free for a feed built around what you actually care about, Dive Deeper research on any story, and the full text of every article.
Create free accountAlready have an account? Sign in