article · Mayo Clinic Proceedings Digital Health
The rapid expansion of artificial intelligence (AI) in health research has generated both considerable enthusiasm and important concerns. While AI offers new opportunities to accelerate discovery, improve prediction, and optimise health system performance, its growing influence also raises critical questions about equity, validity, and real-world applicability, particularly in low- and middle-income countries (LMICs).1,2 In these settings, where structural constraints shape both data availability and healthcare delivery, the implications of adopting AI are especially consequential.
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DOI: 10.1016/j.mcpdig.2026.100380
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