Natural language processing (NLP) has shown potential to extract measurements and their primary descriptors from radiology reports and provide them in a structured format, according to findings published in the Journal of Digital Imaging.

In a world of networked medical devices, it’s not hard to imagine a radiology-heavy cyberattack that is not only malicious but also ingenious.
 

Consolidation has become the name of the game for many private radiology practices, but not everyone wants in. Many unaffiliated groups still prefer the independent side of the playing field, defending their turf by contracting to provide imaging services to hospitals and health systems.

Natural language processing (NLP) can provide significant value by auditing all communications related to critical findings, according to a new study published in the Journal of the American College of Radiology.

Machine learning (ML) can help providers extract all relevant facts from radiology reports in real time, according to a new study published in the Journal of Digital Imaging.

Technologists can provide significant value by assigning protocols for certain CT and MRI examinations, according to a new study published in the American Journal of Roentgenology.

Blockchain technology is gaining popularity throughout the world and could potentially have a significant impact on the medical imaging industry, according to a new analysis published in the Journal of Digital Imaging.

The Machine Learning Challenge on Pneumothorax Detection and Localization will kick-off at the SIIM 2019 Annual Meeting starting June 26 in Aurora, Colorado.