Artificial intelligence which automatically diagnoses lung disease could help to ease winter pressure on hospitals, it has been claimed.
State of the art technology has been developed by researchers from the University of the West of Scotland.
It utilises x-rays to compare scans with a database of images from thousands of patients with pneumonia, tuberculosis and Covid.
The technology then uses a process known as deep convolutional neural network – an algorithm typically used to analyse visual imagery – to make a diagnosis in minutes.
During an extensive testing phase, the technique was found to be around 98% accurate.
Tuberculosis and pneumonia, potentially serious infections which mainly affect the lungs, often require a combination of different diagnostic tests such as CT scans, blood tests, x-rays and ultrasounds.
They can be expensive with lengthy waiting times for results.
The technology developed by UWS was originally created to quickly detect Covid-19 from x-ray images.
It is now hoped that the technology can be used to help relieve winter strain on pressured hospital departments through quick and accurate detection of disease.
The development of the technology was led by Professor Naeem Ramzan, along with UWS PhD students Gabriel Okolo and Dr Stamos Katsigiannis.
Professor Ramzan explained: “There is no doubt that hospital departments across the globe are under pressure and the outbreak of Covid-19 exacerbated this, adding further strain to pressured departments and staff.
“There is a real need for technology that can help ease some of these pressures and detect a range of different diseases quickly and accurately, helping free up valuable staff time.
“X-ray imaging is a relatively cheap and accessible diagnostic tool that already assists in the diagnosis of various conditions, including pneumonia, tuberculosis and Covid-19.
“Recent advances in AI have made automated diagnosis using chest x-ray scans a very real prospect in medical settings.”
Researchers at UWS are now exploring the suitability of the technology in detecting other diseases using x-ray images such as cancer.
Professor Milan Radosavljevic, UWS’s vice-principal of research, innovation and engagement, expressed his excitement about the potential of the technology.
“Hospitals around the world are under sustained stress,” said Radosavljevic.
“This can be seen throughout the UK as our fantastic NHS continues to undergo immense pressure, with hard-pressed medical staff bearing the brunt.
“I am excited about the potential of this innovative technology which could help streamline diagnostic processes and reduce strain on staff.
“It’s another example of purposeful, impactful research at UWS as we strive to find solutions to global challenges.”
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