A new post-stroke care pathway from Viz.ai and Medtronic is associated with significant benefits, including higher patient and clinician satisfaction.

Last summer more than 40% of 121 hospital executives surveyed said their organization had already realized a decent ROI in generative AI. However, a C-suite slice of nearly the same size said it was too soon to know for sure. 

Medical students are broadly familiar with digital health technologies. Relatedly, they believe AI will play a crucial role in the future of healthcare. These are good signs for the advancement of evidence-based medicine. 

Previous NLP algorithms for heart failure looked for certain words or phrases, but this updated model makes decisions based on clinical context. 

Nina Kottler, MD, associate CMO for clinical AI at Radiology Partners, explains the movement toward greater regulation of artificial intelligence and the need to test for bias. 

Wasn’t radiology the fastest medical specialty to embrace and adopt AI? And yet burnout continues to afflict many if not most radiologists. 

Generative AI has a bright future in medical education. That goes not only for medical schools but also for postgraduate settings in which residents and fellows do most of their learning while also caring for patients.

Given the precarious excitement of the moment—or is it exciting precarity?—policymakers and healthcare leaders must set directives guiding not only what to do with AI but also when to do it.