Entering its seventh decade of innovation in all things artificial intelligence, Stanford reflects on the people who made it possible and the milestones along the way.
A statewide quality-improvement project to treat excessive bleeding during childbirth averts $9 million annually in California’s health care costs, a Stanford Medicine-led study found.
The study integrates climate, land use, and socioeconomic data to explain and predict malaria dynamics at the village level. The approach could inform health care practitioners and make control strategies more efficient and cost-effective.
Maps of wildfire hazard suggest higher-income communities are more at risk, but low-income communities across California experience fires more frequently.
By sifting through mothers’ and babies’ health records using a machine-learning algorithm, scientists can predict how at-risk newborns will fare in their first two months of life.
