Hannah Murphy

New research suggests that artificial intelligence-based CT scheduling systems could significantly reduce imaging delays for emergency department patients with concerning symptoms. A new paper in Radiology: Artificial Intelligence details how an AI-driven CT queue prioritization system can improve patients’ time to diagnosis without requiring additional imaging equipment or staffing.

New data support the role of large language models (LLMs) in streamlining quality control initiatives. Published in the Journal of the American College of Radiology, the findings suggest that LLM-based systems can automate the processing of radiology report checks. The study specifically focused on identifying variability in breast ultrasound reports, but experts believe these systems have potential beyond breast imaging alone.

A diagnostic imaging center in Florida recently disclosed that it was the subject of a data breach that could have exposed vulnerable patient information. Saint Pete MRI, a diagnostic imaging and sleep lab in St. Petersburg, Florida, on Wednesday informed patients who may have been impacted by the breach. Notifications letters indicate the breach occurred on or around February 23, 2025.