The simultaneous advances of deep learning and radiomics may soon yield a single unified framework for clinical decision support that has the potential to “completely revolutionize the field of precision medicine.”

An artificial intelligence “super brain” could help eliminate unnecessary diagnostic testing in patients who present with stable chest pain, according to a recent study, potentially saving physicians and patients significant time and money.

The FDA has given 510(k) clearance to an AI alert for urgent finding of a collapsed lung in chest X-rays. The approval is a first for an AI-based chest X-ray solution that can help doctors make quicker diagnoses from one of the world’s most used imaging modalities.

AI can predict death or heart attack better than humans, according to a new study presented at the International Conference on Nuclear Cardiology and Cardiac CT (ICNC) in Lisbon.

Researchers at Duke and in Tanzania have developed an algorithm for discerning the extent of a traumatic brain injury (TBI) in a low-resource setting.

Combing through insurance claims and other health data on more than 72 million U.S. residents, a machine learning algorithm was able to quite accurately identify more than 222,000 individuals who have very early stage Alzheimer’s disease.

As medical devices are increasingly being touched by new AI innovations, the FDA will soon have to grapple with reality of regulating “living things” in a new way, according to a report from Roll Call.

The global excitement around healthcare’s embrace of AI and other developing technologies is not misplaced, but it needs to be tempered by an ongoing watchfulness for misuse.