Data Science Without Borders

A team of data scientists and health institutions across Africa is building a no-code platform that lets clinicians and policymakers run machine-learning models without writing a single line of programming code. The project tackles a practical bottleneck: many African hospitals and health ministries collect patient data, but lack the in-house data scientists needed to turn that data into predictions or decision-support tools. Existing machine-learning tools often require specialist skills, and off-the-shelf models trained on European or American populations can fail when applied to African patient groups. The project will co-design support strategies with seven pathfinder institutions, each at a different stage of data maturity, to ensure the tools fit local needs. If successful, the project could shift how routine care is managed in resource-limited settings. A hospital might use the platform to predict patient deterioration, a ministry could forecast disease outbreaks, or a researcher could analyse treatment outcomes—all without hiring a dedicated data science team. The project also aims to make the platform replicable, so other African institutions can adopt it without starting from scratch.