The Makerere University AI Health Lab is a pioneering research institution focused on harnessing the power of artificial intelligence (AI) to transform healthcare across Africa. Located at one of Africa’s leading universities, the lab brings together a diverse team of researchers, technologists, healthcare professionals, and policy experts dedicated to solving the continent’s most pressing health challenges through AI innovations.
Our work spans a range of critical areas, including AI-driven diagnostics, predictive health analytics, and the development of data-driven solutions aimed at improving access to quality healthcare. We are committed to advancing cutting-edge research while ensuring that AI-powered health technologies are translated into real-world applications that make a tangible difference in people’s lives.
Ocular's 3D printable adapter connects smartphones to microscopes, allowing for easy image capture and alignment in health centers. This technology enhances pathogen identification for diseases like malaria and tuberculosis, supported by a mobile and web application for diagnostic assistance.
We are developing a rapid, low-cost screening system for malaria diagnosis using a 3D printed smartphone adapter for microscopes and deep learning models, aimed at enhancing real-time diagnostics and surveillance in Uganda to improve public health outcomes.
The Lacuna Fund project aims to enhance malaria microscopy diagnosis in low and middle-income settings by generating high-quality, open-labeled blood smear datasets from Uganda and Ghana, using smartphone-mounted microscopes to support machine learning models for detection.
This project aims to enhance cervical cancer detection in Sub-Saharan Africa by curating a labeled digital dataset of 1,000 Pap smear images using a smartphone-mounted microscope, supporting machine learning tasks for early and reliable screening.
We propose an AI-powered ultrasound screening tool to detect high-risk pregnancies early, aiming to reduce maternal mortality in Uganda and similar settings. The solution will integrate clinical, demographic, and imaging data to support timely and accurate diagnosis at the primary healthcare level.
This project aims to support natural resource management in Uganda by using AI to analyze satellite and forestry inventory data for predicting land cover changes and improving decision-making in response to deforestation and climate change.
Level 6, COCIS Block B,
Makerere University,
Kampala - Uganda
+256 704 024 681
info@makerereaihealthlab.com
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