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S3E2 - TB and diagnosis - Using state of the art technology to find and treat people living with TB
- Our guests Jacob Creswell from the STOP TB Partnership and Brenda Mungai from the Liverpool School of Tropical Medicine, provide insight into how technology is playing a key role in TB diagnosis, and highlights from the discussion include:
- The technologies currently available to help diagnose TB
- The role of artificial intelligence (AI) in TB diagnosis
- The involvement of communities in the development of AI and the benefits that people are seeing from these developments
Dr. Jacob Creswell is Head of Innovations & Grants at the Stop TB Partnership. He coordinates the TB REACH initiative which is focused on improving programmatic aspects of tuberculosis case detection and treatment outcomes. He serves as a global expert on different aspects of improving tuberculosis case detection including private sector engagement and active case finding. Jacob is currently working on the introduction of new diagnostic and screening tools for TB including artificial intelligence and how they can fit into more efficient and effective diagnostic algorithms. Jacob has published more than 80 scientific publication and has over 20 years of experience working at Stop TB, WHO and CDC on TB and HIV.
Dr Brenda Nyambura Mungai
PhD candidate, Liverpool School of Tropical Medicine, Director of Tuberculosis and Lung Health Centre for Health Solutions-Kenya
A medical doctor Bachelor’s degree of Medicine and Surgery (University of Nairobi) with a postgraduate diploma in HIV management (Colleges of Medicine South Africa) and a Masters in Tropical Medicine and Infectious Diseases (Liverpool, United Kingdom). She has over fifteen years national and international professional experience in clinical care and public health approaches to management of infectious diseases especially in TB/ HIV in developing countries. Currently pursuing a PhD in Global Health at Liverpool School of Tropical Medicine focusing on operational modelling, and the role of chest X-ray and computer-aided detection software in tuberculosis screening in low -and lower-middle income countries.
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By The SCL Agency- Our guests Jacob Creswell from the STOP TB Partnership and Brenda Mungai from the Liverpool School of Tropical Medicine, provide insight into how technology is playing a key role in TB diagnosis, and highlights from the discussion include:
- The technologies currently available to help diagnose TB
- The role of artificial intelligence (AI) in TB diagnosis
- The involvement of communities in the development of AI and the benefits that people are seeing from these developments
Dr. Jacob Creswell is Head of Innovations & Grants at the Stop TB Partnership. He coordinates the TB REACH initiative which is focused on improving programmatic aspects of tuberculosis case detection and treatment outcomes. He serves as a global expert on different aspects of improving tuberculosis case detection including private sector engagement and active case finding. Jacob is currently working on the introduction of new diagnostic and screening tools for TB including artificial intelligence and how they can fit into more efficient and effective diagnostic algorithms. Jacob has published more than 80 scientific publication and has over 20 years of experience working at Stop TB, WHO and CDC on TB and HIV.
Dr Brenda Nyambura Mungai
PhD candidate, Liverpool School of Tropical Medicine, Director of Tuberculosis and Lung Health Centre for Health Solutions-Kenya
A medical doctor Bachelor’s degree of Medicine and Surgery (University of Nairobi) with a postgraduate diploma in HIV management (Colleges of Medicine South Africa) and a Masters in Tropical Medicine and Infectious Diseases (Liverpool, United Kingdom). She has over fifteen years national and international professional experience in clinical care and public health approaches to management of infectious diseases especially in TB/ HIV in developing countries. Currently pursuing a PhD in Global Health at Liverpool School of Tropical Medicine focusing on operational modelling, and the role of chest X-ray and computer-aided detection software in tuberculosis screening in low -and lower-middle income countries.