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

U.S. Senators Ron Wyden and Cory Booker want to know what government agencies and insurance providers are doing to make sure health systems avoid the use of biased algorithms.

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.

Researchers have developed an AI algorithm that can identify cancer cells in digital pathology images, sharing their findings in EBioMedicine.

AI’s impact on medical imaging continues to be one of the most significant trends of the last several years, and now the FDA has announced a public workshop focused on that very subject.

Deep learning models can improve the detection of attention deficit hyperactivity disorder (ADHD), according to new findings published in Radiology: Artificial Intelligence.

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

A majority of U.S. consumers are confident AI will have a positive impact on both patients and healthcare providers, according to a new report from Blumberg Capital.

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.