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AFRICAI-RI: BUILDING AFRICA’S FIRST FEDERATED IMAGING RESEARCH INFRASTRUCTURE FOR TRUSTWORTHY AI IN MEDICAL IMAGING

A iniciativa reúne 14 instituições de referência da Europa e da África Subsaariana
A iniciativa reúne 14 instituições de referência da Europa e da África Subsaariana

The AFRICAI-RI project, the Pan-African Research Infrastructure for Collaborative Biomedical Imaging and Artificial Intelligence in Respiratory Care, was designed to significantly contribute to improving healthcare in Sub-Saharan Africa through the establishment of the region's first interconnected and multi-institutional medical imaging research infrastructure. The project will capitalize on European and African expertise to adapt data infrastructures and innovative medical imaging solutions to the diverse contexts of  Sub-Saharan Africa, promoting an ethical, inclusive, and sustainable approach to Artificial Intelligence (AI) applied to healthcare.


Funded by the European Commission under the Horizon Europe – Global Health EDCTP3 Joint Undertaking programme, the project officially launched with the aim of establishing the first federated biomedical imaging research infrastructure in Africa. The initiative brings together 14 leading institutions from Europe and Sub-Saharan Africa to promote the development of ethical, trustworthy, and context-adapted AI solutions tailored to the needs of the African continent.


The project is coordinated by Prof Karim Lekadir, ICREA Research Professor and Director of the Barcelona Centre for Artificial Intelligence in Medicine (BCN-AIM) at the Universitat de Barcelona, and by Dinis Nguenha, researcher at the Centro de Investigação em Saúde de Manhiça (CISM).


AFRICAI-RI aims to strengthen African capacity in AI and medical imaging by connecting hospitals, universities, and research centres through a federated, secure and privacy-preserving infrastructure. This approach will enable the collaborative development of AI solutions without the need to centralize sensitive medical data.


According to Karim Lekadir, “AFRICAI-RI represents a major step towards data sovereignty and equitable AI innovation in Africa. Our goal is to build from Africa and for Africa, empowering local researchers and clinicians to lead the development of AI solutions for the continent’s most pressing healthcare and medical imaging challenges.”


The project will address the critical challenges related to infectious diseases and the shortage of medical imaging experts in the region. In its initial phase, the focus will be on tuberculosis (TB) and pneumonia, two of the leading causes of mortality in Africa. In this context, AI-based AI diagnostic tools adapted to African clinical settings will be developed, validated, and implemented. The project will also establish ethical, legal, and governance frameworks to ensure the responsible use of Artificial Intelligence, while aligning with African and European data protection standards.


According to Dinis Nguenha, “we are building more than AI models; we are building a future in which Africa defines the standards for ethical and scalable digital health.”

ABOUT AFRICAI-RI

AFRICAI-RI is a four-year project (2025–2029), funded by the Horizon Europe programme under Global Health EDCTP3 (grant no. 101190731). It is coordinated by the University of Barcelona (Spain) and CISM (Mozambique).


The consortium brings together institutions from several African and European countries, including Delft Imaging Ghana (Ghana), Jimma University Medical Centre (Ethiopia), Centre de Recherche Médicale de Lambaréné (Gabon), Infectious Diseases Research Collaboration (Uganda), University of Kinshasa (Democratic Republic of Congo), Nigerian Institute of Medical Research (Nigeria), Iba Der Thiam University (Senegal), Kamuzu University of Health Sciences (Malawi), Medical Research Council Unit The Gambia (The Gambia), Erasmus Medical Centre (Netherlands), Foundation for Research and Technology (Greece), and the Barcelona Institute for Global Health (Spain).


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Addresses and Contacts

HEADQUARTERS, MANHIÇA, CAMBEVE​ NEIGHBORHOOD

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Tel: (+258) 21 81 01 81 / 21 81 00 02

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