ARTIFICIAL INTELLIGENCE IN AFRICAN CARDIOVASCULAR CARE: OPPORTUNITIES, CHALLENGES, AND PATHWAYS TO IMPROVED OUTCOMES

Abstract

Background : Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality in Africa, accounting for over 1 million deaths annually. This burden is worsened by urbanization, modern lifestyle changes, limited healthcare access, and underreporting due to inadequate diagnostic tools. As CVD prevalence rises, Africa faces challenges in prevention, diagnosis, and management, particularly in rural areas. Addressing this crisis requires innovative approaches, and artificial intelligence (AI) has emerged as a transformative solution. Main Body : AI offers opportunities to revolutionize cardiovascular care by improving diagnostic accuracy and enabling personalized treatments. Predictive analytics, machine learning, and telemedicine can process structured and unstructured data from m-Health applications, wearable devices, and hospital records to facilitate early detection. Advanced applications, such as genome-wide association studies (GWAS) and precision medicine, further enhance genetic analysis and optimize treatment. Despite its advantages, AI integration faces challenges, including inadequate infrastructure, high implementation costs, and limited digital literacy among healthcare providers. Data privacy concerns remain critical, with only 36 of 55 African countries enacting data protection laws. Policy and funding constraints further hinder AI adoption, especially in rural areas. Conclusion : To overcome these barriers, Africa must develop ethical standards for data use, invest in workforce training, and strengthen healthcare infrastructure. Public-private partnerships and global collaborations are essential for capacity building and securing funding. Also, successful AI applications in some African countries and around the world can be modeled across Africa to improve cardiovascular health outcomes.