Charles E. Kahn Jr., MD, MS, professor and vice chair of the department of radiology at the University of Pennsylvania’s Perelman School of Medicine in Philadelphia, has been named the editor of RSNA’s new online journal, Radiology: Artificial Intelligence.

Automated and clinical breast density evaluation methods are equally accurate in predicting a patient’s risk of breast cancer, according to a new study published in Annals of Internal Medicine.

Charles Kahn, MD, MS, has been named editor of Radiology: Artificial Intelligence, a new online journal set to launch in early 2019, according to an announcement from the Radiological Society of North America (RSNA)'s Board of Directors.

The American College of Radiology and the Medical Image Computing and Computer Assistance Intervention (MICCAI) Society announced last week a partnership to develop artificial intelligence (AI) algorithms to better meet radiologists' clinical needs.

The FDA has recently approved iSchemaView’s RAPID CTA, a new 3D imaging technology for computed tomography (CT) angiography, according to a May 1 press release.

In a diagnostic imaging lab at Case Western Reserve University in Cleveland, Anant Madabhushi, professor of biomedical engineering, has seen his deep learning computers beat humans at diagnosing heart failure, detecting cancers and determining their strength—but he knows these tools can’t replace his team.

Anant Madabhushi, PhD, a professor at Case Western Reserve University in Cleveland, has led significant deep learning research in recent years, but he doesn’t necessarily think this evolving technology will replace radiologists and pathologists any time soon.

The American College of Radiology (ACR) Data Science Institute (DSI) and Society for Imaging Informatics in Medicine (SIIM) are joining forces on May 30 to host the Spring 2018 Data Science Summit: Economics of Artificial Intelligence (AI) in Health Care.