A new framework combining machine learning and radiomics will help distinguish between low- and high-risk prostate cancer, according to new research published in Scientific Reports.

As the healthcare industry shifts to providing more personalized care, the precision medical imaging market could see tremendous growth thanks to new technologies, such as AI and deep learning, clinical decision support software, sensors, 3D printing and precision analytics, according to a report from Frost & Sullivan.

An AI algorithm helped determine adult women’s brains are, on average, a few years younger than the brains of males of the same age, according to research published in the Proceedings of the National Academy of Sciences.

A deep learning model classified acute and nonacute pediatric elbow abnormalities on radiographs in trauma with 88 percent accuracy, according to new research published in Radiology: Artificial Intelligence. 

AI for image analysis is predicted to be the top digital health technology for 2019 based on a survey of healthcare professionals, according to Forbes.

Russian researchers and radiologists have developed AI software that can distinguish and subsequently mark lung cancers on a CT scan within 20 seconds. 

Companies developing machine-learning solutions for medical imaging have received more than $1.2 billion in capital investments since 2014, according to a report by Signify Research.

Researchers have trained an AI algorithm to identify and locate radius and ulna fractures on wrist radiographs with 98 percent sensitivity and 73 percent specificity, on a per study basis. Their findings were published in the Radiological Society of North America’s new journal Radiology: Artificial Intelligence.