ChatGPT is only so-so at letting physicians know if any given clinical study is relevant to their patient rosters and, as such, deserving of a full, time-consuming read. On the other hand ...
Imperfect algorithms. Resistant clinicians. Wary patients. Divisive disparities. The plot ingredients of a flashy techno-thriller coming to a cineplex near you? No—just a few of the many worries that provider organizations take on when they move to adopt AI at scale.
People have been anticipating the demise of radiologists for years, speculating that AI will soon be interpreting imaging results with the precision of a seasoned veteran.
The COVID crisis has significantly increased the volume of data healthcare providers are rushing into the cloud. This “smash and grab” behavior is largely explained by the spike in healthcare workers doing their jobs remotely.
Researchers at Boston’s Beth Israel Deaconess Medical Center are sharing insights they gained while building a locally focused, AI-aided model for anticipating COVID-19’s next moves.
A new scientific statement from the American Heart Association explores the many ways AI and machine learning are being used to improve care for heart patients.