WEDNESDAY, Jan. 23, 2019 — An artificial intelligence (AI) system can analyze chest X-rays and spot patients who should receive immediate care, researchers report.
The system could also reduce backlogs in hospitals someday. Chest X-rays account for 40 percent of all diagnostic imaging worldwide, and there can be large backlogs, according to the researchers.
“Currently, there are no systematic and automated ways to triage chest X-rays and bring those with critical and urgent findings to the top of the reporting pile,” explained study co-author Giovanni Montana. He is formerly of King’s College London and is now at the University of Warwick in Coventry, England.
Montana and his colleagues used more than 470,300 adult chest X-rays to develop an AI system that could identify unusual results.
The system’s performance in prioritizing X-rays was assessed in a simulation using a separate set of 15,887 chest X-rays. All identifying information was removed from the X-rays to protect patient privacy.
The system was highly accurate in distinguished abnormal from normal chest X-rays, researchers said. Simulations showed that with the AI system, critical findings received an expert radiologist opinion within an average of 2.7 days, compared with an average of 11.2 days in actual practice.
The study results were published Jan. 22 in the journal Radiology.
“The initial results reported here are exciting as they demonstrate that an AI system can be successfully trained using a very large database of routinely acquired radiologic data,” Montana said in a journal news release.
“With further clinical validation, this technology is expected to reduce a radiologist’s workload by a significant amount by detecting all the normal exams, so more time can be spent on those requiring more attention,” he added.
The researchers said the next step is to test a much larger number of X-rays and to conduct a multi-center study to assess the AI system’s performance.
The U.S. National Heart, Lung, and Blood Institute has more on chest X-rays.
Posted: January 2019
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