Artificial Intelligence

A new AI algorithm developed by researchers at Case Western Reserve University can predict which malignant breast cancers will progress and benefit from additional treatment.

“Our broad radiology community has a unique opportunity to engage with this exciting scientific evolution, working with interdisciplinary ‘convergence science’ teams,” Andrea Rockall, clinical chair of radiology, Imperial College London, wrote in a new editorial.

Facebook and NYU Langone Health announced their commitment to making MRI scans more efficient through the use of AI more than one year ago, and a new story from Popular Science provides a glimpse into what the two have been up to.

“Machine learning is a low-cost and efficient tool that could help physicians arrive to a quicker decision as to how to approach an indeterminate nodule,” lead author of the study, John Eisenbrey, PhD, said.

The commercially available algorithm helped residents improve their sensitivity at spotting abnormal findings in chest x-rays.

“Given the large number of people who suffer from traumatic brain injury every day and are rushed to the emergency department, this has very big clinical importance," study authors said.

BI-RADS 4 lesions are considered among the most difficult and suspicious category of breast lesions.

“With the ability to understand each of the different domains and translate between the experts in these domains, imaging informaticists are now essential players in the development, evaluation and deployment of AI in the clinical environment.”

Trained on nearly 1 million screening mammography images, researchers from New York University found their algorithm could push radiologists’ ability to accurately identify breast cancer to nearly 90%.

"The AI we use works almost like magic—and it will help radiologists save lives," said Antonio Sze-To, a postdoctoral fellow who worked on the project.

Santa Clara, California-based NVIDIA and King's College London are teaming up to create a new federated learning system to advance medical imaging research.

Deep learning offers similar detection of prostate cancer on MRI compared to prostate imaging reporting and data system (PI-RADS) assessments, according to new research out of Germany.