Chest X-rays are routinely performed to diagnose and monitor a wide range of conditions affecting the lungs, heart, bones, and soft tissues. Ensuring that abnormal X-rays showing signs of urgent illness are reviewed by a radiologist as soon as possible means patients get the most appropriate care promptly and improve treatment outcomes.
The researchers from King’s College London trained an algorithm to recognise abnormalities in chest X-rays, using a dataset of 500,000 anonymised adult chest X-rays from patients at Guy’s and St Thomas’, which had been assessed by expert radiologists. By applying this algorithm to such a large number of chest X-rays, the artificial intelligence (AI) system was able to interpret the visual patterns on the X-rays, predict their urgency and suggest a priority level for the X-rays to be reported by a radiologist.
The team then tested the AI system in a simulation and found it could dramatically reduce the time it takes to ensure abnormal chest X-rays receive expert radiologist opinion, cutting the reporting time from 11 days to less than 3 days.
This is just one of the many projects that King’s researchers are working on at a new collaborative Centre, The London Medical Imaging and AI Centre for Value-Based Healthcare.