A team at the University of Toronto has successfully developed artificial intelligence (AI) that helps automate the radiation therapy planning process, potentially saving radiologists from several days of work on just one patient.

The global market for artificial intelligence (AI) in medical imaging is expected to see significant growth in the years ahead, topping $2 billion by 2023, according to a new report from Signify Research.

RSNA announced Wednesday, August 1, that it has big plans for educating members about artificial intelligence (AI) and machine learning (ML) for 2018 and beyond.

Artificial intelligence (AI) is an immensely popular topic in radiology, sparking countless discussions and debates about whether it will give radiologists a new tool for providing high-quality patient care or end up replacing them altogether.

Sham Sokka, PhD, has spent the bulk of his career in radiology, where he’s worked for 15 years with a range of clients to shape and customize imaging modalities, workflows and software.

Researchers have shown that they can use artificial intelligence (AI) to restore low-quality photos by exposing a neural network to only other low-quality photos, according to work presented at the International Conference on Machine Learning in Stockholm.

As the influence of artificial intelligence (AI) continues to grow in radiology, the specialty must come together to re-examine its ethics and code of behavior, according to a new commentary published in the Journal of the American College of Radiology.

Researchers have developed a fully integrated computer-aided diagnosis (CAD) system that detects, segments and classifies masses from mammograms using deep learning and a deep convolutional neural network (CNN), according to a new study published by the International Journal of Medical Informatics.