To date, research pertaining to reactive lymphadenopathy has focused mostly on patients with cancer who are routinely staged and monitored via PET/CT or in women undergoing breast cancer screening and/or imaging with mammography and ultrasound.

“We found that if you tune the classical methods, they can perform very well,” an expert involved in the research said.

Three medical journals are investigating possible manipulation of data in heart studies led by researchers from Temple University that found favorable health impacts of blood thinners.

In an effort to perhaps dissuade skepticism among medical students who are on the fence about the future of radiologists, experts in the field recently offered a detailed overview of the use of AI in imaging.

The National Institutes of Health (NIH) has launched a new artificial intelligence (AI) program, backed by $130 million in funding, that aims to expand the use of AI in the biomedical and research communities.

In particular, the experts paid close attention to instances of extrathyroidal extension (ETE) on ultrasound. 

A new artificial intelligence system can detect active tuberculosis on chest radiographs with accuracy comparable to radiologists, a recent paper in Radiology reports. 

A new analysis offers a detailed comparison of soft-tissue lymphomas and soft-tissue tumors based on imaging characteristics from MRI scans—an area of study that has not yet been rigorously explored, the authors of the paper indicated.