Challenges of Artificial Intelligence in Medical Diagnosis in Congolese Hospitals: A Literature Review

Abstract

Introduction: Artificial intelligence (AI) is rapidly transforming medical diagnosis worldwide, but its adoption remains limited in Africa, particularly in the Democratic Republic of Congo (DRC). This narrative review aims to analyze the contributions, challenges, and prospects for integrating AI into medical diagnosis in the DRC. Methodology: A comprehensive literature review was conducted in February 2025 in PubMed, Web of Science, Scopus, and Google Scholar databases, as well as reports from international organizations. Studies on the use of AI in medical diagnosis in resource-limited countries, particularly in Africa, were included without language restrictions. The selection followed a two-step process (title/abstract then full text); 103 articles were retained for qualitative synthesis. Results: Studies show that AI enables a 12%-15% improvement in diagnostic accuracy in radiology and a 20% reduction in exam interpretation time. It also helps accelerate epidemic detection (30%-50% faster than conventional methods) and overcome the shortage of specialists in rural areas. However, its implementation in the DRC is hampered by the lack of digital infrastructure, insufficient training, and the absence of an appropriate regulatory framework. Maintenance and financing issues still limit the effective use of available systems. Conclusion: AI represents a major opportunity to strengthen medical diagnosis in the DRC, improving the speed and quality of care. However, effective integration requires targeted investments in infrastructure, training, and regulation. The development of national pilot projects and a solid ethical framework are essential steps for gradual and sustainable adoption.

Ähnliche Arbeiten