AI draws conclusions from interventional radiology adverse events data, helping docs design interventions

Radiology Business August 23, 2024
Marty Stempniak

A large language model can analyze massive amounts of interventional radiology safety data and draw conclusions, helping IR specialists to design interventions.

Large volumes of medical device adverse event data accumulate daily, University of Toronto experts detailed in the Canadian Association of Radiologists Journal [1]. In 2022 alone, U.S. Food and Drug Administration databases recorded nearly 3 million incidents, with most reports collected in a free-text field.

“When attempting to generate meaningful insights from such databases, human analysis is limited by multiple factors like expertise, time required, lack of uniformity, and fatigue,” Blair E. Warren, a radiology resident in the university’s Department of Medical Imaging at the time of the study, and colleagues wrote Aug. 21. “Consequently, databases that...

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