Makerere AI Health Lab

Makerere University · Kampala, Uganda

Lab22 peopleDiagnostics & medical imagingMaternal & child health

Lab profile

About Makerere AI Health Lab

The lab develops AI-powered diagnostic tools, curated datasets, and research partnerships to support diagnosis, disease surveillance, and health systems strengthening in low-resource African settings. Work focuses on building locally-owned, clinically-validated AI solutions for malaria, tuberculosis, cervical cancer, and maternal health that are designed around existing clinical workflows and infrastructure constraints.

Diagnostics & medical imagingMaternal & child healthHealth datasetsResponsible AISurveillance & population healthHealth systems strengtheningAutomated microscopyEnvironmental & planetary health

01 · Research focus

Research areas and highlights

Topics and recent work as stated on the lab’s own site.

  • The Ocular ProjectA 3D printable smartphone-to-microscope adapter with mobile and web applications for automated malaria and tuberculosis screening.
  • Automated Mobile Microscopy for Malaria Diagnosis and Surveillance in UgandaDeveloping a rapid, low-cost malaria screening system using 3D printed smartphone adapters and deep learning models for real-time diagnostics and surveillance.
  • Datasets for AI-Based Diagnosis of MalariaGenerating high-quality, open-labeled blood smear datasets from Uganda and Ghana using smartphone-mounted microscopes to support machine learning models.
  • Curating a Dataset of Digital Pap Smear Images for Automated Cervical Cancer Screening in UgandaCurating a labeled digital dataset of 1,000 Pap smear images using smartphone-mounted microscopes for machine learning-based cervical cancer screening.
  • A Machine Learning-aided Platform for Point-of-Care Pregnancy Risk Assessment from 2D UltrasoundAn AI-powered ultrasound screening tool integrating clinical, demographic, and imaging data to detect high-risk pregnancies early.
  • Datasets for Artificial Intelligence-Based Solutions in Predicting Land Use/Cover Changes in UgandaUsing AI to analyze satellite and forestry inventory data for predicting land cover changes to support natural resource management.

02 · People

Leadership and researchers

People listed on the lab’s team pages, by role.

Rose NakasiDirector · Pricinpal InvestiatorLinkedIn ↗
Sylvia Nabukenya-KazoobaSenior Researcher Ethics

03 · Research intelligence

Research Intelligence evidence

Publications, grants and clinical trials linked to the lab’s researchers in Health AI Central’s research data.

04 · Updates

Updates and lab news

News and events from the lab’s own site.

No news has been collected from the lab’s site yet.

05 · Official presence

Lab sources and channels

The lab’s own pages and accounts.