Nvidia has released a new series of products aimed to accelerate the research and development of artificial intelligence (AI), with one focused on medical imaging, according to a recent article by Forbes.

New artificial intelligence research from Google, presented at MIT Technology Review's EmTech Digital 2018 conference in San Francisco, may point to reducing the number of radiologist-annotated images required to train a deep learning algorithm for medical imaging applications.

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.

A team of physicists in China has used ghost imaging to make detailed x-ray images they claim has lowered the radiation dose by a “million times" compared to previous attempts using the technique, Science Magazine reports.

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.

A group of U.S. researchers created a natural language processing (NLP) system which outperformed traditional rule-based methods in identifying lumbar spine findings, according to a study published online in Academic Radiology.

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.

Jensen Huang, CEO of Nvidia, a California-based technology company, recently revealed plans to construct a medical imaging supercomputer affectionately named Clara.