This breakthrough could help providers pinpoint other neurological conditions, experts noted in a study published Wednesday, Dec. 11, in Radiology: Artificial Intelligence. 

More than 5 million people are diagnosed with skin cancer in the U.S. each year, and an overwhelming majority are categorized as either basal or cutaneous squamous cell carcinoma.

AI can automatically assess if patients show signs of emphysema, according to a new study published in Radiology.

A new imaging technique that uses deep learning technology can identify tumors in colorectal tissue samples with 100% accuracy, according to findings published in Theranostics.

More healthcare providers are starting to investigate how AI can improve patient care, but many of them hurt their own chances of success by making costly mistakes. We spoke with numerous AI vendors about some of the most common mistakes they see being made today. 

AI models can be trained to evaluate chest x-rays as well as radiologists, according to a new study published by Radiology. Specialist-approved reference standards played a crucial role in the team’s research.

"Researchers have been studying the possible link between hair dye and cancer for a long time, but results have been inconsistent," said co-author Alexandra White, PhD.

Healthcare institutions are encountering a growing number of gadolinium deposition disease cases. One expert recently discussed why radiologists should use current data to shed light on the topic and minimize their liability risk.