Mechanical engineers and surgeons from the University of Hong Kong have recently developed what could be the world's first neurosurgical robotic system that can perform bilateral stereotactic neurosurgery on a patient inside an MRI machine.

A convolutional neural network (CNN) model performed as well as clinicians in classifying the area of concern in retinal fundus images and provided evidence for why those choices were made—a common problem for artificial intelligence (AI) technology.

Radiologists are “significantly influenced” by contextual bias when interpreting mammograms, according to a new study published in the Journal of Medical Imaging.

MIT researchers have developed an artificial intelligence-(AI) based algorithm that can register three-dimensional (3D) images 1,000 times more quickly than standard medical image registration techniques.

Researchers from the Massachusetts Institute of Technology (MIT) in Cambridge have been studying a machine learning algorithm they say makes the process of medical image registration more than 1,000 times faster.

The semi-automated, quantitative 3D approach—joint space mapping (JSM)—detects small changes in joints and is both accurate and precise in measuring joint space compared to traditional two-dimensional (2D) radiography.

It’s long past asking “if” artificial intelligence (AI) and related technologies will revolutionize healthcare. According to a recent survey, 80 percent of executives expect AI will be integrated into the patient experience within two years. At the same time, 81 percent of respondents agree their organizations are not ready for the societal and liability issues that will result from this change.

The American Medical Association (AMA) has passed a policy addressing "augmented intelligence"—and not "artificial intelligence"—that provides recommendations for stakeholders' concerns.