Sifting the literature for real-world challenges thwarting adoption of clinical AI across medicine, a team of biomedical engineers and computer scientists has identified and fleshed out an exemplary use case.

The Food and Drug Administration has approved a new drug that claims to slow the progression of Alzheimer’s disease. The drug is the first approved for Alzheimer’s disease since 2003.

The vast majority of healthcare executives say digital transformation across their organizations is accelerating, according to a recent survey of 399 executives from six countries.

Deficiencies in healthcare systems are emerging in states with some of the fastest growing populations.

Healthcare AI has potential not only for neutralizing its inherent algorithmic bias but also for personalizing its outputs to help humans address health inequities.

Black-box AI should be barred from reading medical images in clinical settings because machine learning, like human thinking, tends to take diagnostic shortcuts. 

When the network interpreted complete videos from 42 consecutive patients, it boosted detection rates by as much as 50% over physician-alone reads.

Upon examining a skin lesion they suspected of being malignant, few dermatologists—only 8%—would hold back from performing a biopsy if an AI tool disagreed, classifying it as benign.