AI-powered TB screening project aims to transform diagnosis
A new research project called AddiCAD is combining AI-powered chest X-ray analysis with biomarker blood tests to improve tuberculosis diagnosis. The initiative aims to provide faster and more accurate testing in resource-limited settings.
Why it matters
This technology could significantly reduce undiagnosed TB cases and improve healthcare outcomes in regions with limited medical infrastructure.
A new international research project led by Stellenbosch University (SU) aims to transform tuberculosis (TB) diagnosis by combining artificial intelligence (AI) with a simple finger-prick blood test to improve detection in areas with limited access to healthcare.
The project, known as AddiCAD, will combine AI-powered chest X-ray analysis with a biomarker blood test that measures the body's immune response to TB, offering a faster and potentially more accurate way to identify people with the disease.
Funded with R46 million (€2.5 million) by the Global Health European and Developing Countries Clinical Trials Partnership 3 (Global Health EDCTP3), the initiative officially launched in May and brings together researchers and organisations from South Africa, Namibia, The Gambia and Europe.
Despite being preventable and curable, tuberculosis continues to place a heavy burden on healthcare systems, particularly in low-resource settings.
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