Updated large language models have been trained to process both text- and image-based questions, potentially making them more effective in radiology settings.
In the years since the turn of the century, interventional radiology has made quantifiable strides toward familiarizing the general public with the specialty and, along the way, helping IR better compete for business with surgery.
In a study of more than 250 COVID-positive patients with a history of any cancer, fewer than half the cohort had chest CT findings deemed typical for COVID-related pneumonia based on an RSNA classification guide.
The radiologist who received, in one patient’s view, a mere “slap on the wrist” for missing a couple dozen breast cancers over several years is back in the news.
Whatever specific shape work takes in the near and distant future, it’s likely the COVID-19 era will be looked back upon as a before-and-after dividing line.
The model augmented and significantly improved diagnostic performance for abdominal subspecialists as well as residents—a result researchers say has major clinical implications.
The Society of Radiographers recently indicated that many students had approached them about discriminatory practices occurring during their clinical training.
Has point-of-care ultrasound outpaced hospitals’ capacity to incorporate the technology without anointing any particular specialty its proper guardian? The case could be made.
