One of the main goals of Med-PaLM 2 is to “synthesize information like X-rays and mammograms to one day improve patient outcomes.” 

A new paper details how a team at the University of California utilized a hybrid system consisting of a quality coordinator and NLP software to bring in more than $60,000 in additional revenue from follow-up imaging alone.

“Healthcare is going to change. Writing is going to change. Research is going to change. I’m just trying to publish now and show it so people can know about it and explore more.” 

As artificial intelligence continues to cement itself into radiology workflows, a new analysis offers a detailed look at how radiology programs are adapting curriculum to reflect the impending changes. 

Radiologists interpreting screening mammograms may be especially susceptible to falling victim to automation bias, as these exams are repetitive in nature.

This is the first study to use paired, real-world clinical CT images to evaluate deep learning-based artifact reduction techniques.

Radiologist David Gruen, MD, discusses some of the overarching themes from the Healthcare Information Management Systems Society's annual meeting.

The recently FDA-cleared program merges patient-specific information from prostate imaging, biopsies and pathology, resulting in a deep learning algorithm that creates an AI-generated 3D map of cancer.