Limits and Inadequacies of Artificial Intelligence in Radiology and Medical Imaging in Cameroon: An Analysis of Structural and Technological Barriers

At a time when Silicon Valley is touting the merits of AI capable of detecting cancerous tumors with greater accuracy than the human eye, a pressing question arises for developing countries. The advent of artificial intelligence (AI) has radically transformed global radiology, offering unprecedented opportunities for early diagnosis and workflow optimization to improve patient management and the quality of care. However, its application in middle-income countries, and specifically in Cameroon, faces major structural barriers. This article aims to examine the current inadequacy of AI solutions in Radiology and Medical Imaging within the Cameroonian context. To achieve this objective, we analyze infrastructural disparities, data management challenges, economic constraints, and the training of human resources capable of understanding, analyzing, and utilizing AI. Although AI offers theoretical and practical potential to address the shortage of radiologists, we argue that its hasty deployment without local adaptation risks exacerbating health inequalities.