University of the West of Scotland (UWS) has developed a new, state-of-the-art method of accurately diagnosing Covid-19 using AI.
The UWS AI tech utilises x-ray technology, comparing scans to a database of around 3,000 images belonging to patients with Covid-19, healthy individuals, and people with viral pneumonia.
It is hoped that the University of West of Scotland-developed tech can eventually be used to help relieve strain on hard-pressed Accident and Emergency departments, particularly in countries where PCR tests are not readily available.
The tech uses an AI process known as deep convolutional neural network – an algorithm typically used to analyse visual imagery, to make a diagnosis. During an extensive testing phase, the technique proved to be more than 98% accurate.
Leading the project, Professor Naeem Ramzan, Director of the Affective and Human Computing for SMART Environments Research Centre at UWS, said: “There has long been a need for a quick and reliable tool that can detect Covid-19, and this has become even more true with the upswing of the omicron variant.
“Several countries are unable to carry out large numbers of Covid tests because of limited diagnosis tools, but this technique utilises easily accessible technology to quickly detect the virus.
“Covid-19 symptoms are not visible in x-rays during the early stages of infection, so it is important to note that the technology cannot fully replace PCR tests.
“However, it can still play an important role in curtailing the viruses spread especially when PCR tests are not readily available.
The team now plans to expand the study on UWS AI tech, incorporating a greater database of x-ray images acquired by different models of x-ray machines, to evaluate the suitability of the approach in a clinical setting.