Oncopole, a Montreal-based research center, announced that five teams won the Onco-Tech Competition and will receive a total of $1.97 ($2.6 million CAD) in funding.

Researchers have developed an AI algorithm that can identify cancer cells in digital pathology images, sharing their findings in EBioMedicine.

Deep learning models can improve the detection of attention deficit hyperactivity disorder (ADHD), according to new findings published in Radiology: Artificial Intelligence.

Researchers from the Yale Center for Health and Learning Games are hoping they can keep some teenagers from vaping with an assist from virtual reality (VR).

A healthcare AI startup whose product scours EMRs to quickly find qualified patients for clinical trials has raised $17 million in Series A funding.

For RSNA’s Radiology journal, AI was one of the most popular topics of 2019.

The American College of Radiology (ACR) Data Science Institute (DSI) has created a new resource for radiology researchers: a full list of FDA-cleared AI algorithms related to medical imaging.  

The Mark Foundation for Cancer Research (MFCR) has contributed funding to eight different research projects that involve AI.

Machine learning can help predict the life expectancy of heart failure patients, according to new research published in the European Journal of Heart Failure.

AI can identify patients at risk of dying—of any cause—within the next year or of developing an irregular heartbeat, according to two new studies to be presented at the American Heart Association’s Scientific Sessions 2019.

Working closely with AI has led researchers from one institution to embrace a familiar piece of technology that may surprise many of their peers: the USB drive.

Gilead Sciences, a Foster City, California-based biopharmaceutical company, is scheduled to present new AI-powered research related to nonalcoholic steatohepatitis (NASH) at The Liver Meeting 2019 in Boston.