Physicians with no coding experience are able to create AI algorithms to classify medical images at levels comparable to state-of-the-art platforms, according to a new study published in The Lancet Digital Health. However, some experts questioned whether those without experience should really be creating such technology.

“Assessing (prostate cancer) PCa invasiveness as early as possible is essential for disease management, treatment choice, and patient prognosis,” wrote the authors of a new study published in Clinical Radiology.

A new MRI technique out of the Hebrew University of Jerusalem (HUJI) can show the molecular makeup of the brain, potentially helping clinicians diagnose neurodegenerative diseases such as Alzheimer’s.

AI is central to many large technology companies such as Facebook and Google, and may soon have a similar role in the medical imaging world, argued a group of radiologists in a new editorial published in Clinical Imaging.

Why do some dogs hunt while others herd? The connection between brain structure and function is well-known in both humans and canines, but new research published in the Journal Neuroscience offers new insight into the relationship between innate brain wiring and learned behavior.

Researchers from the University of Oxford have created a new biomarker based off of coronary CT angiography (CCTA) images that can select patients at a high risk of heart attack five years before they occur.

A new radiomics-based machine learning model can evaluate immunohistochemistry (IHC) features and CT images to predict the presence of thyroid nodules, according to a new study published in the American Journal of Roentgenology.

Engineers from Duke University have harnessed the power of machine learning to increase the resolution of optical coherence tomography (OCT) imaging, according to an Aug. 19 study published in Nature Photonics.