As precision medicine transforms disease treatment into a patient-by-patient art and science, AI is poised to help quickly identify or even predict genetic mutations, pointing the way to highly targeted therapies.

Omega Medical Imaging’s FluoroShield gained FDA clearance this month, becoming the first AI-enabled radiation reduction technology to hit the market.

The majority of recent journal studies evaluating the performance of AI algorithms failed to adequately validate test results, according to a meta-analysis published in the Korean Journal of Radiology, meaning most of that research can only serve as proof-of-concept and might not translate into clinical performance.

AI is poised to make a sizable impact on healthcare this year, but we’ll likely see the greatest dent in the areas of medical imaging, diagnostics and suicide risk prediction, according to data presented at the Partners HealthCare World Medical Innovation Forum in Boston.

A rare and difficult-to-diagnose genetic condition that raises LDL (bad) cholesterol to dangerous levels is now vulnerable to an AI tool.

As incidents producing mass casualties can occur anywhere at any time, leadership at trauma centers of all levels do well to prepare. A good place to start is learning from the experiences of urban hospitals dealing with shooting victims every day or close to it.

Researchers have identified an approach for more accurately diagnosing schizophrenia using AI, bringing some objectivity to the field of neurodevelopmental disorder diagnosis, according to a study published in the May edition of Artificial Intelligence in Medicine.

A deep learning model trained on more than 1.5 million electrocardiograms and developed by a team at the Mayo Clinic improved detection rates for hyperkalemia in patients with chronic kidney disease (CKD), according to a study published April 3 in JAMA Cardiology.