AI-driven x-ray scanning machines could drastically reduce diagnosis waiting times

New research has shown that future x-ray machines will be powered by artificial intelligence to help diagnose chest abnormalities, also easing pressure on staff.

The software will utilise machine learning and computer vision to speed up the detection of abnormalities, flagging up any issues and urgently referring patients on for diagnoses.

Scientists involved in the research believe the system could reduce the time to receive an opinion from the current average of eleven days down to less than three.

Professor Giovanni Montana of the University of Warwick and leader of the research team, said “Artificial intelligence-led reporting of imaging could be a valuable tool to improve department workflow and workforce efficiency.

“The increasing clinical demands on radiology departments worldwide has challenged current service delivery models, particularly in publicly-funded healthcare systems.

“It is no longer feasible for many radiology departments with their current staffing level to report all acquired plain radiographs in a timely manner, leading to large backlogs of unreported studies.

“In the United Kingdom, it is estimated that at any time there are over 300,000 radiographs waiting over 30 days for reporting.

“The results of this research shows 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 – particularly for chest radiographs which account for 40 per cent of all diagnostic imaging performed worldwide.”

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Posted by Tony May, Partner/head of Clinical Negligence Department, Chadwick Lawrence LLP (tonymay@chadlaw.co.uk ), medical negligence lawyers and clinical negligence solicitors in Huddersfield, Leeds, Wakefield and Halifax, West Yorkshire.

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