Taking geographical luck out of emergency care with AI [Video]

By Yuna Nakayasu and Tinglong Dai, Johns Hopkins University

In the heart of winter, a quiet but isolated village in Hokkaido, Japan, faces a stark reality faced by many rural communities worldwide: the difficulty of accessing emergency medical services when every second counts. For elderly residents like Mr. Sato, experiencing symptoms of a stroke, the distance is more than geographic – it could imperil life-saving treatment.

This scenario is far from unique; research indicates that poor access to emergency medicine, especially due to longer distances to hospitals, is associated with higher mortality rates. Compounding the geographic challenge is an acute shortage of medical professionals and essential diagnostic services in rural areas. Moreover, significant disparities in access exist for vulnerable populations, defined not only by their rural location, but also by their insurance status and income.

The combined effect of these challenges is a dangerous gap in emergency care that artificial intelligence solutions can help fill. Now imagine a local health worker using a portable CT scanner …