Role of Artificial Intelligence in Strengthening the TB Diagnostic Cascade

Regent Court building courtyard

Event details

12:00 - 13:00


Mary Kagujje - TB Clinical Care Specialist, Centre for Infectious Disease Research in Zambia

Abstract: Despite being both preventable and curable, over 10 million people develop TB every year, and over 1.5 million people die from TB annually. Unfortunately, only 61% of estimated TB patients are diagnosed and put on treatment. Timely and accurate diagnosis of TB is essential for effective patient management, early treatment initiation, and containment of transmission. However, the currently available TB screening and diagnostic methods have their limitations, necessitating innovative solutions to bolster the diagnostic cascade. This talk will explore the biggest gaps in the TB diagnostic cascade, currently available TB screening and diagnostic tools and their limitations, current and potential applications of AI in the TB diagnostic cascade, and challenges and limitations associated with AI implementation, emphasizing the importance of rigorous validation.

Biography: Mary's research focus is TB diagnostics and case finding. She has been an investigator on two TB REACH grants which have collectively assessed the performance of all the current WHO approved TB screening tools and selected TB diagnostic tests in the Zambian setting. These projects have also assessed some non-approved TB tests including GeneXpert on oral swabs and FujiLAM. Mary’s manuscript “Active case finding in a high burden setting; comparison of facility and community-based case strategies in Lusaka, Zambia”, was one of the resources used to inform the Zambian strategy on active TB case finding. Additionally, she contributed to the only TB patient pathways study in Zambia and the National TB care cascade. She is currently a member of the Zambia national TB technical working group.


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