As the use of artificial intelligence continues to proliferate in healthcare, radiologists may be opening themselves up to a whole new set of liability concerns.

Xiang Li, PhD, with Massachusetts General Hospital’s Department of Radiology, and colleagues showed their platform could identify pneumothorax when tested on scans with and without the condition, doing so in less than three minutes per scan.

Machine learning models using radiomics can help radiologists classify renal cell carcinomas (RCCs), according to new findings published in the American Journal of Roentgenology.

Hospitals of the future will operate very differently than today thanks to the boom in AI, according to the American Hospital Association.

A new AI platform takes a mere 10 seconds to identify key findings on a patient’s chest x-ray, compared to the 20 minutes typically required.

Numerous imaging societies, including the American College of Radiology (ACR) and RSNA, have published a new statement on the ethical use of AI in radiology.

J. Raymond Geis, MD, senior scientist at the ACR Data Science Institute, spoke with HealthImaging about the recently published multisociety statement on ethical AI in radiology.

“The radiology community needs an ethical framework to help steer technological development, influence how different stakeholders respond to and use AI, and implement these tools to make the best decisions for—and increasingly with—patients," said one of the paper's lead contributors, Raymond Geis, MD.