Artificial intelligence that automatically diagnoses lung diseases could help ease winter stress in hospitals, it is claimed.
The state-of-the-art technology was developed by researchers at the University of the West of Scotland.
It uses X-rays to compare scans with a database of images from thousands of patients with pneumonia, tuberculosis and Covid.
The technique then uses a process called a deep convolutional neural network — an algorithm commonly used to analyze visual images — to make a diagnosis within minutes.
During an extensive testing phase, the technique was found to be about 98 percent accurate.
Tuberculosis and pneumonia are potentially serious infections that primarily affect the lungs and often require a combination of different diagnostic tests, such as CT scans, blood tests, X-rays, and ultrasounds.
They can be expensive, with long wait times for results.
The technology developed by UWS was originally intended to rapidly detect Covid-19 from X-ray images.
The hope is now that the technology can be used to help relieve winter stress in stressed hospital departments by quickly and accurately detecting disease.
The development of the technology was led by Professor Naeem Ramzan and UWS PhD students Gabriel Okolo and Dr Stamos Katsigiannis.
Professor Ramzan explained: “There is no doubt that hospital sectors across the globe are under pressure, and the Covid-19 outbreak has exacerbated that pressure, putting further pressure on stressed departments and staff.
“There is a real need for technology that can help relieve some of these stresses and detect a range of different diseases quickly and accurately, helping to free up valuable staff time.
“X-ray imaging is a relatively inexpensive and easy-to-use diagnostic tool that is already helping diagnose a variety of diseases, including pneumonia, tuberculosis and Covid-19.
“Recent advances in artificial intelligence have made the use of chest X-ray scans for automated diagnosis a very real prospect in the medical setting.”
UWS researchers are now exploring the technology’s applicability in detecting other diseases using X-ray images, such as cancer.
Professor Milan Radosavljevic, UWS Vice-Chancellor for Research, Innovation and Engagement, expressed excitement about the potential of this technology.
“Hospitals around the world are under constant pressure,” Radosavlevich said.
“This can be seen across the UK as our fantastic NHS continues to be under enormous pressure, with stressed medical staff bearing the brunt.
“I’m excited about the potential of this innovative technology to help simplify the diagnostic process and reduce stress for employees.
“This is another example of purposeful, impactful research at UWS as we work to find solutions to global challenges.”