The president of Portable Radiology Services in North Canton, Ohio has been indicted for defrauding Medicare and Medicaid of nearly $2 million for billing x-ray services that were never rendered, reported Cleveland 19 News.

“Because this language model can so rapidly adapt to existing training labels, these results should not be considered the final work but rather a foundation upon which iterative improvement can be performed,” wrote the author of a new study published in the Journal of the American College of Radiology.

Carestream recently signed three multi-year contracts for  more than $25 million to implement its Vue Clinical Collaboration Platform and digital radiography solutions for healthcare facilities in the Emilia Romagna, Liguria and Molise regions of Italy.

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

“With information obtained from this study, it is possible that neuroimaging in newborns may to some extent predict neurodevelopment even for healthy children, and prenatal intervention targeted at improving white matter integrity at birth will be important for further promoting neurodevelopment in children,” wrote researchers of a new Radiology study.

Experts have theorized that ultra-marathon runners may face negative cardiovascular changes due to their extreme training methods. A team of Polish-led researchers used cardiovascular MR (CMR) to investigate this, publishing their findings in the European Journal of Radiology.

Nearly one million patients per year in the United States require treatment for plantar fasciitis, according to authors of a new study published in Academic Radiology.

Aaron Williams was 16 years old when he committed suicide on the campus of his Charleston, South Carolina, high school in 2010. It was only until after the tragedy that neuroimaging revealed multiple lesions in his brain.

Hitachi’s first overseas project for the Multi-Ion Particle Therapy System.

Machine learning can reduce a radiologists workload by lowering the number of screening mammograms they’re required to read while preserving accuracy, according to results of a feasibility study published in the Journal of the American College of Radiology.