Call for papers highlights the need for AI data from LMICs to improve global health outcomes.
Brain health is an emerging global challenge, which has strong implications for the development and implementation of artificial intelligence (AI) in medicine. To date, advances in medicine driven by data from high income countries have shaped everything downstream: what conditions are studied, what populations are enrolled, what tools are validated. This is a problem beyond simple underrepresentation; it is a problem of algorithmic drift. The algorithms generated by AI will not be adequately trained for lower-and middle-income country (LMIC) scenarios unless data from LMICs make their way into the algorithm. Bridging this algorithmic gap requires publication of locally generated, interpreted, and context-specific evidence from LMICs to ensure representation from the majority of the global population.
No takes yet. Share an insight, caveat, or question.
Kathleen M Hayden (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: