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AI lung diagnosis technique could help ease winter strain

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Winter

AI that automatically diagnoses lung diseases such as tuberculosis (TB) and pneumonia could ease winter pressures on hospitals, according to researchers at University of the West of Scotland (UWS).

TB and pneumonia are potentially serious infections that often require a combination of different diagnostic tests, such as CT scans, blood tests, X-rays and ultrasounds.

However, these tests can be expensive and often come with lengthy waiting times for results.

Researchers at UWS initially initially developed the pioneering technique to quickly detect Covid-19 from X-ray images.

The technique compares X-ray scans to a database of thousands of images from patients with pneumonia, tuberculosis and Covid.

It then uses a deep convolutional neural network – an algorithm typically used to analyse visual imagery – to diagnose the images.

During an extensive testing phase, technique proved to be 98 per cent accurate in identifying a range of different lung diseases in a matter minutes.

It is hoped that the technology can help to ease strain on pressured hospital departments through the quick and accurate detection of disease.

Professor Naeem Ramzan, Director of the Affective and Human Computing for SMART Environments Research Centre at UWS, said:

“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.”

By freeing up radiographers continuously in high demand, the technology could help reduce waiting times for test results and create efficiencies within the testing process.

Professor Milan Radosavljevic, UWS’s Vice-Principal of Research, Innovation and Engagement, said:

“Hospitals around the world are under sustained stress.

“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.”

UWS researchers are now exploring the suitability of the technology in detecting other diseases using X-ray images, such as cancer.

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