Connected health data and AI that serve patients
I work on making health records speak to each other and on testing where AI can improve care in resource-limited clinics.
What I do
- Electronic health record standards and semantic interoperability
- Ontology and fuzzy-logic models for health data
- AI for maternal and public health, including federated learning
- Evaluation of health technologies in Kenyan counties
Evidence from my work
- Lead author, "The role of AI in reducing maternal mortality: current impacts and future potentials. Protocol for an analytical cross-sectional study", PLOS ONE (2025), with M. S. Shisanya, B. Mayeku and L. N. Namusonge. The protocol describes a mixed-methods evaluation of two AI tools across ten Kenyan counties; results are not yet published.
- Two 2025 papers on EHR standards and semantic interoperability, and a fuzzy ontological model
- Africa UniNet researcher on a school mental-health project
Supervision and examination
One completed PhD on semantic interoperability; examined theses on HIV treatment interruption, diabetes prediction and IoT-based patient consultation.
Partners and funders
County health departments and global-health AI groups are natural partners; Strathmore University.
Sustainable Development Goals
- SDG 3 (good health and well-being)
- SDG 9
- SDG 10
Collaboration ideas
- Interoperability for county health information systems
- Federated models that work across clinics with limited data
- Evaluation of AI tools for maternal and child health
Related areas
Let us build something together
Whether you are a funder, a university looking for a partner, or a doctoral applicant, I would like to hear from you.
Collaborate with me