AI can identify women at a high risk of developing breast cancer more accurately than existing prediction models, according to a new study published in Radiology.

AI is almost certain to have a monumental impact on radiology, but what, exactly, will that mean for radiologists?

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.

MaxQ AI has achieved ISO 27001 certification, meaning the Tel Aviv, Israel-based company fully complies with the internationally recognized information security standard.

Siemens Healthineers has announced the arrival of two new AI-based software assistants designed to help radiologists interpret MRI examinations. The solutions were officially introduced to the public at RSNA 2019 in Chicago.

The rise of AI is one of the most popular topics in all of radiology, but there are still clear limits to its potential.

RSNA announced the winners of its third annual AI competition, the RSNA Intracranial Hemorrhage Detection and Classification Challenge, at RSNA 2019 in Chicago.

Zebra Medical Vision has received FDA clearance for an AI solution designed to identify pleural effusion in chest x-rays.

Deep learning-based prediction models can help healthcare providers diagnose small pulmonary nodules, according to a new study published in Academic Radiology.

For RSNA’s Radiology journal, AI was one of the most popular topics of 2019.