The technique analyzes standard pre-contrast cardiac MRIs to produce “virtual contrast” images resembling enhanced ones.  

Radiologists who utilize artificial intelligence support may be vulnerable to automation bias, which can deteriorate their performance over time. 

This can be achieved without sacrificing image quality and could offer providers the same diagnostic accuracy as full-length scans that take between 15 and 45 minutes. 

Members of the Childhood Cancer Caucus are proposing the Accelerating Innovation for Kids Act, aimed at fast-tracking the deployment of this tech in pediatrics. 

A new analysis offers insight into how the decision to implement AI can affect an organization’s clinical efficiency and financial health, suggesting these decisions do not always offer the ROI vendors promise.

Disclosing the utilization of AI is not enough to ensure the integrity of manuscripts, the editor-in-chief of a prominent radiology journal cautions.

Although it's well-established that lesions in the brain’s gray matter play a significant role in the progression of multiple sclerosis, there has been no reliable way to visualize these abnormalities on imaging.

Researchers recently sought to better understand how patients perceive rapidly evolving advancements in AI, sharing their findings in RSNA’s Radiology. 

While the technology remains investigational in many practices, researchers say it has the potential to improve diagnostic accuracy, streamline AI development and strengthen radiology quality assurance.

The health network, which operates 37 hospitals in California, drastically reduced scheduling delays after integrating an FDA-cleared algorithm designed to speed up imaging acquisition times.  

New Neiman research explores how Medicare's New Technology Add-On Payment has impacted use of an AI triage tool for pinpointing severe strokes.