The diagnosis and treatment of a gut disease that can cause permanent damage in children can be sped up by the application of machine learning, according to researchers from the University of Virginia schools of Engineering and Medicine.

Radiology is the medical specialty most conducive to clinical AI applications. After all, the pre-AI technique of computer-aided detection has been used in mammography since 1998, for example. So it shouldn’t come as a surprise to find AI “app stores” rising in radiology.

Deep learning could help catch drug dealers who use social media to connect with customers, according to a study conducted at UC-San Diego and published June 14 in the Journal of Medical Internet Research.

AI is aiding in the diagnosis of several diseases and health risks, and researchers have recently found that machine learning can help predict the onset of psychosis, a debilitating mental disorder that can compromise an individual’s psychology and their ability to think and feel.

BlackThorn Therapeutics, a clinical-stage neurobehaviorial health company, has raised $76 million in a Series B funding round, the company announced June 13.  

Harvard researchers have used machine learning to predict which patients soon to undergo an operation for low-back pain should be monitored for opioid dependence down the road.

AI in Healthcare caught up with Humana's new CMO William Shrank, MD, MSHS, to talk about the changing role of the CMO, the rise of AI in healthcare and how technology is helping Humana shape its integrated care goals as a major Medicare Advantage provider.

The American Medical Association is pushing for policies around AI in healthcare that don’t penalize physicians who avoid the technology while it’s still in a state of flux on so many fronts, from regulatory oversight to clinical usefulness.

Assistive robots used in medical settings could inspire caregivers—familial as well as professional—to treat patients more empathetically and patiently, potentially improving outcomes.

Combining AI with advances in acoustic engineering, Australian researchers have developed an algorithm that can help diagnose common pediatric respiratory conditions such as asthma, croup and pneumonia.