Lung diseases like tuberculosis and pneumonia can be diagnosed in a matter of minutes using artificial intelligence – and university researchers have said the technology could be key in easing winter pressures on hospitals.
Developed by the University of the West of Scotland, the technology originally created to quickly detect Covid-19 from X-ray images has been proven to automatically identify a range of different lung diseases.
Professor Naeem Ramzan, researcher at the Scottish university, said: “Systems such as this could prove to be crucial for busy medical teams worldwide.”
Recent advances in AI have made automated diagnosis using chest X-ray scans a very real prospect in medical settings.— Professor Naeem Ramzan
Tuberculosis and pneumonia – potentially serious infections which mainly affect the lungs – often require a combination of tests like CT scans, blood tests, X-rays and ultrasounds to diagnose.
But these tests can be expensive and time consuming.
Researchers hope the technology can be used to relieve winter strain on pressurised hospital departments through the quick and accurate detection of disease.
Prof Ramzan said with pressures put on hospitals across the globe by the coronavirus there was a “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,” said the director of the Affective and Human Computing for Smart Environments Research at the university.
“Recent advances in AI have made automated diagnosis using chest X-ray scans a very real prospect in medical settings.”
The technology uses X-rays, then compares the scans to a database of thousands of images from patients with pneumonia, tuberculosis and Covid.
It then uses a process known as deep convolutional neural network, an algorithm typically used to analyse imagery, to make a diagnosis.
The university said the technique had proven to be around 98% accurate, and researchers at the institution are now looing into using the technology to detect other diseases using X-ray images like cancer.
