Shanghai researchers have created an artificial intelligence (AI) system designed to identify people most at risk for developing type 2 diabetes, according to a report by the South China Morning Post.

A deep convolutional neural network (DCNN) can be trained to analyze MRI scans and differentiate between tuberculous spondylitis and pyogenic spondylitis, according to a new study published in Scientific Reports.

A new algorithm that can automatically map CT scan locations of patients on computational human phantoms may trump manual mapping techniques for patient dose monitoring, clinical trials and epidemiologic studies, detailed a study published online Sept. 5 in the Journal of Digital Imaging.

Toronto-based Exact Imaging and Cambridge, U.K.-based Cambridge Consultants have announced a new international partnership focused on improving the way specialists visualize and detect prostate cancer.

Why do some people feel more pain than others? Using fMRI, researchers at Wake Forest School of Medicine in Winston-Salem, North Carolina, found the answer may lie in mindfulness, according to recent research published in PAIN.

The creators of a fully automated medical image analysis program to detect breast tumors was inspired by the classic video game Tetris. It is also almost twice as fast at finding lesions as existing techniques and just as accurate.

An automated medical image analysis program developed by researchers—deriving its functionality from Tetris, the widely known puzzle-piece video game—can identify breast cancer twice as quickly as existing methods, according to a Sept. 6 release from the University of Adelaide in Australia.  

A deep learning system (DLS) designed to assess liver fibrosis using CT images was found to be highly accurate, according to a new study published in Radiology.