AI-based system to cut process time for abnormal chest X-rays
Artificial Intelligence-led reporting of imaging could be a valuable tool to improve department workflow and workforce efficiency.
London: A novel Artificial Intelligence (AI)-based system can dramatically reduce the time needed to process abnormal chest X-rays with critical findings -- cutting the average delay from 11 days to less than three days, say researchers.
The research team, led by Professor Giovanni Montana at the University of Warwick, found that normal chest radiographs were detected with a positive predicted value of 73 per cent and a negative predicted value of 99 per cent -- at a speed that meant that abnormal radiographs with critical findings could be prioritised to receive an expert radiologist opinion much sooner than the usual practice.
"Artificial Intelligence-led reporting of imaging could be a valuable tool to improve department workflow and workforce efficiency," said Montana.
"The results show that alternative models of care, such as computer vision algorithms, could be used to greatly reduce delays in the process of identifying and acting on abnormal X-rays," Montana added in a paper published in the journal Radiology.
"The application of these technologies also extends to many other imaging modalities including MRI and CT," the researchers added.