Authors
O A Ajagbe, T A Olagunju, P A Ekhaiyeme, O E Dada, K Onah
Published in
Journal of cancer policy. Pages 100815. Oct 13, 2026. Epub Oct 13, 2026.
Abstract
Cancer registries are the cornerstone of population level cancer surveillance, providing the data necessary to estimate burden, monitor trends, and evaluate cancer control programmes. In low- and middle-income countries (LMICs) like Nigeria, these registries face overwhelming challenges, including limited geographic coverage, poor data acquisition, inadequate infrastructure, and constrained workforce capacity, all of which undermine data quality at a time of a looming cancer burden. This review assesses the current state of Nigerian registries, spearheaded by the pioneer University College Hospital (UCH), Ibadan registry, established in 1962, and examines the landscape of artificial intelligence (AI) applications that can transform operations through automated data abstraction, improved record linkage, and real time surveillance. Using a narrative synthesis of published literature and international guidelines, the review finds that while AI models such as machine learning and natural language processing show great promise for enhancing efficiency, fragmented health information systems, limited digitization, and weak governance frameworks hinder their deployment in LMICs. Strengthening these systems requires a dual strategy of structural reform and phased technological innovation. Policy level interventions, including legal mandates for registration, sustainable domestic financing, and appropriate AI governance, are essential to transform passive data repositories into intelligent surveillance systems and ensure equitable improvements in cancer control across Nigeria and comparable settings.
PMID:
42869180
Bibliographic data and abstract were imported from PubMed on 14 Oct 2026.
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