Description
Background
Cancer is a leading cause of mortality in Kenya, with late-stage diagnosis and limited decision support contributing to poor outcomes. Although registries and health records capture substantial data, their use for real-time decision-making remains limited. To address this gap, we developed an AI-enabled platform leveraging Generative AI and Retrieval-Augmented Generation (RAG) to enhance decision support, surveillance, and research.
Methods
The system comprises three interoperable components:
(1) A FHIR-compliant mobile app that allows clinicians to capture structured patient data and receive AI-generated clinical recommendations based on national guidelines;
(2) A public health dashboard that visualizes cervical and breast cancer trends, highlights regional disparities, and supports data-driven policymaking;
(3) A research portal that enables interaction with both structured and unstructured data, allowing researchers and policymakers to generate insights using natural language queries.
The platform prioritizes offline usability, transparency, and modular design for scalability.
Results
The platform was demonstrated at the 2025 National Cancer Summit to approximately 100 participants. Feedback emphasized the importance of aligning data entry with national standards, integrating with existing health systems, and supporting frontline health workers with context-specific recommendations. Additional themes included usability of the app, interest in expansion to other cancers, and the need for sustainable financing models..
Conclusion
This innovation demonstrates how global advances in AI can be adapted to Kenya’s context through local co-design, empowering local health systems to transform cancer care.By strengthening clinical decision-making, improving national surveillance, and enabling research, the platform represents a scalable model for cancer care.
| Country | Kenya |
|---|---|
| Organization | Private Sector |
