Can AI improve healthcare in resource-limited settings without massive budgets or billion-parameter models?
Patricia Thaine sits down with Chenjerai Sisimayi, a clinical epidemiologist and data scientist based in Zimbabwe, and Tariq Khokhar, Head of Data for Science and Health at the Wellcome Trust. Together, they explore what it actually takes to build and deploy AI tools in healthcare systems across low and middle income countries.
The conversation cuts through the hype to focus on practical realities: How do you train a model when you only have 500 chest X-rays? What happens when you remove an AI tool from clinicians who've grown dependent on it? And why might a simple checklist outperform a sophisticated algorithm?
Chenjerai shares his work developing hybrid deep learning models for TB and COVID-19 classification using local data, and the challenges of integrating these tools into clinical workflows. Tariq brings perspective from large-scale trials, including the UK's EDITH mammography study, and raises critical questions about evaluation, unintended consequences, and what "good value for money" actually means in healthcare AI.
They also dig into often-overlooked infrastructure gaps: the lack of systematic language data collection for African languages, the promise of "small AI" approaches built on transfer learning, and why national AI strategies matter for getting these tools into practice.
Chenjerai Sisimayi is a Zimbabwe-based Clinical Epidemiologist and Data Scientist with two decades of experience working across Africa at the intersection of health, data, and innovation. He has supported governments, development partners, and private-sector organisations in applying analytics and technology to strengthen health systems and improve population outcomes.
Tariq Khokhar is Head of Data for Science and Health and Chief Data Scientist at the Wellcome Trust, a role he has held since 2019. He leads a team of experts who support innovations in data and AI that advance Wellcome’s strategies in discovery science, mental health, infectious disease and climate and health. He brings deep expertise in data science, innovation, and public policy, with experience spanning industry, multilateral institutions, non-profits and philanthropy. Prior to Wellcome, he served as Chief Data Scientist and Managing Director at The Rockefeller Foundation and as Senior Data Scientist and Global Data Editor at the World Bank. Earlier in his career, he held roles including Open Data Evangelist at the World Bank and Technology Innovation Analyst at Development Initiatives. He also served as Chief Development Officer and Director at Aptivate, a non-profit focused on technology for international development. Tariq is currently a Trustee of UK Biobank and formerly Chair of the Board of Trustees at DataKind UK.
