Use of artificial intelligence for health science in low- and middle-income countries: NIH portfolio landscape, gaps and opportunities

Key Points

• To explore the NIH portfolio of AI-enabled health research in low- and middle-income countries, identifying gaps and opportunities.
• Analysis of NIH investment in AI health research focusing on low- and middle-income countries.
• Assessment of priority areas such as outbreak detection and disease surveillance.
• Evaluation of ethical considerations, data governance, and collaboration in AI health studies.
• Increased NIH investment in AI-enabled health research globally, particularly in LMICs.
• Identified key health areas in need of AI solutions, like diagnostics and remote care.
• Emphasized the importance of ethical standards and infrastructure for sustainable AI health applications.