“This study implies that future clinical workflows may see AI be used in an adjunct capacity to improve interpretations of CT scans by helping call radiologists' attention to findings that may be overlooked.” 

Stamatia Destounis, MD, a radiologist and managing partner at Elizabeth Wende Breast Care in Rochester, New York, chair of the American College of Radiology (ACR) Breast Commission, explains the rapid adoption of 3D mammogram digital breast tomosynthesis (DBT) technology.
 

Society of Breast Imaging President John Lewin, MD, explains some of the new initiatives and technology in mammography that are designed to increase early breast cancer detection.

Monique Rasband, vice president of imaging, cardiology and oncology, KLAS Research, explains some of technology trends KLAS researchers have found in enterprise imaging system and radiology artificial intelligence (AI).

Charles Kahn, Jr., MD, editor of the the journal Radiology: Artificial Intelligence, and professor and vice chair of radiology at the University of Pennsylvania Perelman School of Medicine, explains the work involved integrating AI in radiology systems and the role of AI in augmenting patient care.
 

Charles E. Kahn, Jr., MD, MS, editor of the the RSNA  journal Radiology: Artificial Intelligence, and professor and vice chair of radiology at the University of Pennsylvania Perelman School of Medicine, discusses the need to validate AI algorithms with your own patient population data.  

The addition of computer-aided diagnostic generated MRI series could help radiologists identify clinically significant prostate cancer more frequently. 

An artificial intelligence system that is currently commercially available for use in adults could also have applications in a pediatric population, according to a new study in Pediatric Radiology.