Artificial intelligence and clinical practice in Africa: what every healthcare professional should know
Artificial intelligence (AI) is rapidly becoming an essential driver of transformation in health systems worldwide. In Africa, where shortages of human resources, unequal access to care, and manual management of patient records remain widespread challenges, AI has the potential to offer concrete solutions to strengthen the efficiency, quality, and equity of health services.
AI in Africa: a unique context, specific needs
Africa faces rapid population growth and an epidemiological transition that is increasing the prevalence of chronic diseases, while the physician-to-population ratio remains among the lowest globally (0.2 doctors per 1,000 inhabitants in 2020). Despite unevenly distributed digital infrastructure in the health sector, AI adoption in Africa is progressing, driven by local initiatives and international partnerships.
Clinical applications of AI: from diagnosis to patient management
• Diagnostic support:
AI tools are already being used to detect diseases earlier and/or with greater accuracy. For example, a project at Université Iba Der Thiam de Thiès leverages deep learning to enable early diagnosis of liver fibrosis, providing a diagnostic tool tailored to low-resource settings.
• Medical decision support:
In Kenya, the mDaktari virtual clinic application is integrating ChatGPT to enhance the quality and accessibility of healthcare by using advanced language models and anonymized patient data to support clinicians and efficiently respond to patient needs in low-income communities.
• Telemedicine and automated triage:
AI can facilitate patient triage and admissions. In Senegal, Haskè Health has implemented an AI-supported admission system in primary care to assess symptoms, prioritize care, and reduce wait times, improving patient experience and easing the workload on medical teams.
AI for non-clinical tasks: saving time and enhancing efficiency
• Administrative and organizational management:
Solutions like "Afya Rekod," developed in Kenya, offer a digital health platform that uses AI for patient health data analysis and reporting, enabling efficient medical record management and improved patient care.
• Data analysis and planning:
AI enables rapid analysis of local epidemiological trends. For instance, Gaston Berger University in Saint-Louis uses AI and satellite imagery to map schistosomiasis risk areas, allowing for targeted health interventions and better resource allocation.
• Continuous training and access to information:
Platforms such as Medical Learning Hub (MLH), developed in Senegal, integrate AI language models to generate personalized assessment questions based on clinical guidelines, enhancing ongoing training for health professionals and their understanding of care standards. In Cameroon, a multilingual chatbot provides real-time health information in local languages, facilitating health literacy even offline.
Challenges and precautions: what every professional should keep in mind
• Data quality and representativeness:
AI algorithms must be trained on African data to avoid bias.
• Confidentiality and security:
Protecting patient data is crucial. Countries must establish standards to ensure the confidentiality and security of medical information, which is vital for maintaining patient trust and upholding ethical standards.
• Complementarity, not substitution:
AI should be viewed as a support tool, not a replacement for clinical judgment. These tools can assist decision-making but do not substitute for human expertise.
• Training and support:
Adopting AI requires ongoing education. It is crucial for African health professionals to seek to strengthen their knowledge and skills in the use of AI in medical practice.
Taking action: how to get involved today
• Participate in AI in health training or webinars.
• Test tools suited to your context.
• Exchange with colleagues.
• Contribute to local data collection: The more African professionals participate in building representative databases; the more relevant AI solutions will be for the continent.
AI is not a miracle solution, but it represents a unique opportunity to overcome some of the structural barriers that hinder access to quality care in Africa. Whether already a user or simply curious, African health professionals must take ownership of these tools, seek training, and actively participate in this revolution.
Healthcare professionals in Africa and around the world have the responsibility to shape AI that is ethical, inclusive, and adapted to the realities of their communities.
What are your thoughts ?
This newsletter post is written by Dr. Anifa Kalay, founder of KALKIS Health Solutions/Solutions en Santé KALKIS, a social enterprise based in Ottawa.
Its mission is to contribute to addressing health inequalities in Canada and around the world by providing educational resources for healthcare professionals and researchers , as well as consulting services in health project development and management for organizations and individuals.