Pairing multispectral optoacoustic tomography with ultrasound provided biomarker information that may better diagnose patient's with autoimmune diseases and thyroid nodules.

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.