Artificial Intelligence | August 2019

Machine learning algorithms can classify pathology reports and help providers track follow-up imaging recommendations, according to new findings published in Radiology: Artificial Intelligence.

Using deep learning models to triage screening mammograms can improve radiologist specificity without hurting sensitivity, according to new research published in Radiology.

Deep learning can improve the accuracy and efficiency of digital breast tomosynthesis (DBT) examinations, according to new findings published in Radiology: Artificial Intelligence.

RSNA announced Wednesday, July 31, that it would be expanding its AI Showcase at RSNA 2019 in Chicago.

Researchers have developed a convolutional neural network (CNN) that predicts long-term mortality from a single chest x-ray, according to new findings published in JAMA Network Open. 

Machine learning models could help some patients with suspected pulmonary embolism (PE) avoid unnecessary CT imaging, according to new findings published in JAMA Network Open.

Convolutional neural networks (CNNS) can detect urinary tract stones on unenhanced CT scans with significant accuracy, according to new findings published in Radiology: Artificial Intelligence.

Fujifilm SonoSite announced Tuesday, July 30, that the company is collaborating with Boston-based Partners HealthCare to develop AI-powered portable ultrasound solutions.