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Poster
in
Workshop: 3rd Workshop on practical ML for Developing Countries: learning under limited/low resource scenarios

From MICCAI to AFRICAI: African Network for Artificial Intelligence in Biomedical Imaging

Karim Lekadir · Celia Cintas · Noussair Lazrak · Jihad Zahir · Tinashe Mutsvangwa · Mohammed El Hassouni · Mustafa Elattar · Islem Rekik · Madete June · Julia Schnabel · Yunusa Garba Mohammed


Abstract:

Over the recent years, there has been excitement about the extraordinary opportunities that artificial intelligence may offer in tomorrow’s healthcare. Given the potential of AI technology in facilitating the quantification of large and complex datasets, medical imaging has witnessed rapid and revolutionary developments. However, a limitation of current AI developments for medical imaging is that they have overwhelmingly, and almost entirely, targeted imaging applications in highincome settings. Hence, it is important to promote and accelerate the development of trustworthy and accessible AI solutions for medical imaging in low-to-middle income countries –an urging need to advance global healthcare. This paper describes the authors’ experience and initiatives in promoting AI for medical imaging on the African continent, by Africans for Africans. First, the paper will discuss MICCAI 2024, the first international conference on medical image computing and computer assisted intervention that will be taking place on the continent. Subsequently, we will present AFRICAI, a new African network dedicated to research, education and cooperation in the field of AI in imaging and radiology. With this paper, we hope to raise awareness about these initiatives and attract more collaborators, promote new research and innovation in the field to address Africa-specific healthcare challenges, and encourage similar initiatives for promoting practical AI solutions for developing countries in Africa and beyond.

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