Equitable Health Intelligence: Reclaiming Diagnostic Sovereignty Through Innovationology and Noesology in African Health Systems

The integration of Artificial Intelligence (AI) into global healthcare systems has revolutionized diagnostic accuracy and speed. Yet, in African contexts, this transformation remains marked by structural marginalization and epistemic dissonance. AI-driven diagnostics, largely developed in the Global North, often operate on clinical models and datasets that exclude African genomic, phenotypic, and cultural realities. This results in diagnostic errors, algorithmic bias, and the perpetuation of algorithmic colonialism. This article introduces the paradigm of Equitable Health Intelligence (EHI)—a framework that transcends technical efficiency to address ontological justice, contextual relevance, and data sovereignty in African diagnostics. Drawing from Innovationology and Noesology, we argue for a pluriversal approach to medical intelligence—one that integrates indigenous epistemologies, relational care logics, and collective intelligence systems. The paper synthesizes empirical research from Kinshasa (DRC) and Kisumu (Kenya), proposes the Moleka Grid for pluralistic diagnostic architecture, and offers a blueprint for a Pan-African Health AI Charter. Ultimately, we reframe diagnostics not as a neutral act of detection, but as a deeply political, cultural, and ethical process central to epistemic sovereignty and health justice in Africa.