A team of Ohio State University radiologists have developed artificial intelligence (AI) that can not only analyze hundreds of CT scans within minutes, but can detect the presence and urgency of hemorrhages, masses, hydrocephalus and stroke, according to the university’s paper, the Lantern.

Seattle radiologist Maria Chong, MD, a body imaging specialist for Radia, said in a new interview that artificial intelligence (AI) and machine learning will “revolutionize radiology” in the next decade.

As the influence of artificial intelligence (AI) and machine learning (ML) continues to spread throughout medical imaging, radiology training programs may need to update their curricula and prepare for both the short- and the long-term effects of these new technologies, according to a new commentary published in Academic Radiology.

Nvidia, a Santa Clara, California-based technology company, announced the winners of its Inception contest for the best artificial intelligence (AI) startups at this year’s GPU Technology Conference (GTC) in San Jose. One of those winners, Subtle Medical, is focused on improving medical imaging by improving exam times and costs.

Ever since artificial intelligence (AI) became one of the biggest topics in radiology, there has been a debate about whether AI would eventually replace radiologists.

Artificial intelligence might be a hot tech topic, but it could also pose ethical risks—namely racial ones—to healthcare, Clinical Innovation + Technology reported this month.

A novel machine learning model could accurately predict which men might benefit most from additional imaging before a prostate biopsy, saving patients both money and discomfort, a new study states.

Few radiologists understand the relationship between radiology and artificial intelligence (AI) quite like Keith Dreyer, DO, PhD, vice chairman and associate professor of radiology at Massachusetts General Hospital in Boston.