The potential role of AI improving health care delivery in low- and middle-income countries (LMICs).

Abstract

This paper explores the transformative potential of artificial intelligence (AI) in enhancing healthcare delivery in low- and middle-income countries (LMICs), focusing on its applicability, challenges, and pathways for integration. The study is structured around three core objectives: examining current AI applications in Low- and Middle-Income Countries and their potential adaptations; investigating how AI can address pressing health challenges such as resource allocation and disease management; and identifying barriers to AI adoption, including technological infrastructure, data privacy concerns, and workforce training deficits. AI technologies have demonstrated significant efficacy in diagnostics, disease surveillance, and resource optimization, exemplified by mobile health (mHealth) solutions that extend healthcare access to underserved populations. However, the successful implementation of AI in LMICs is impeded by insufficient data quality, lack of robust infrastructure, and ethical considerations. By drawing on lessons from developed nations and emphasizing public-private partnerships, this study proposes strategies to overcome these obstacles, ensuring that AI can be harnessed effectively to improve health outcomes. The findings highlight the need for context-specific AI solutions and collaborative efforts among stakeholders to realize the full potential of AI in achieving equitable and efficient healthcare systems in LMICs.