Groundbreaking AI Technology Accurately Diagnoses COVID-19 Using Chest X-Rays in Minutes

A pioneering artificial intelligence (AI) technology is capable of accurately diagnosing COVID-19 in just a few minutes.

The groundbreaking program developed by researchers at University of the West of Scotland (UWS; Scotland, UK) is able to detect the virus far more quickly than a PCR test; which typically takes around two -hours. It is hoped that the technology 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 state-of-the-art technique utilizes 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 then uses an AI process known as deep convolutional neural network, an algorithm typically used to analyze visual imagery, to make a diagnosis. During an extensive testing phase, the technique proved to be more than 98% accurate. The team now plans to expand the study, 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.

“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,” said Professor Naeem Ramzan, Director of the Affective and Human Computing for SMART Environments Research Centre at UWS, who led the team behind the project. “Several countries are unable to carry out large numbers of COVID tests because of limited diagnosis tools, but this technique utilizes 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. It could prove to be crucial, and potentially life-saving, when diagnosing severe cases of the virus, helping determine what treatment may be required,” added Professor Ramzan.

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University of the West of Scotland