AI finds unmapped regions in need of health services

Machine-learning analyses of satellite images can help identify communities needing healthcare services in some of the most remote parts of the planet, according to a study published Aug. 14 in the Journal of the American Medical Informatics Association.

The work was led by researchers at the Icahn School of Medicine’s Arnhold Institute for Global Health in New York City.

Senior study author Prabhjot Singh, MD, PhD, and colleagues homed in on clusters of buildings in southeastern Libya, which has vast swaths of largely inhospitable terrain, after the sites had been identified as probable sites of community-level activities by a deep-learning algorithm.