ArticleGlobalization and health2025
The impact of artificial intelligence (AI) on maternal mortality: evidence from global, developed and developing countries.
Article in Globalization and health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- A conceptual framework for measuring AI health equity.International journal for equity in health · 2026Article
- Beyond the 'Pregnancy Black Box': a global roadmap for artificial intelligence-driven pharmacogenomics in maternal-neonatal health.The pharmacogenomics journal · 2026Review
- The economic imperative of artificial intelligence in maternal and neonatal health: a review of evaluation benefits, frameworks, challenges, future perspectives, and limitations.Cost effectiveness and resource allocation : C/E · 2026Review
- Artificial intelligence and the future of maternal and newborn health in low-income countries: advancing equity, early detection, and health system resilience.Frontiers in public health · 2026Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study examines the impact of Artificial Intelligence (AI) on maternal mortality in alignment with Sustainable Development Goal (SDG) 3.1, which aims to reduce maternal mortality to below 70 per 100,000 live births by 2030. Despite advancements, maternal mortality remains disproportionately high in developing countries due to weaker healthcare infrastructure.
methodsUsing panel data from 70 countries (1990-2022), sourced from WHO's Global Burden of Disease (GBD), World Bank's World Development Indicators (WDI), UNCTAD, and the World Robotics database, we apply the Difference-in-Differences (DiD) approach to assess AI's impact over time and the Auto-Regressive Distributed Lag (ARDL) model to examine short- and long-term effects.
resultsAI adoption significantly reduces maternal mortality, particularly in developing countries, where post-2000 advancements have led to notable declines. ARDL results show that 27% of deviations from long-term maternal mortality trends are corrected annually, highlighting AI's sustained impact. The DiD analysis indicates AI's greatest benefits in resource-limited settings, including improving early diagnostics, personalized care, and remote monitoring. In developed countries, AI's effects are marginal due to existing advanced healthcare systems.
conclusionAI presents a transformative solution for reducing maternal mortality, particularly in low-resource settings. Policymakers should prioritize AI-driven healthcare, expand digital infrastructure, and ensure equitable access to maximize its benefits. AI integration is crucial for addressing maternal health disparities and accelerating progress toward SDG 3.1.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.