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New AI-based Test Uses X-rays to Detect COVID-19 Rapidly

by Angela Mohan on Jan 22 2022 12:03 AM

New artificial intelligence (AI) based test uses X-rays to accurately diagnose COVID-19 in just a few minutes.

New AI-based Test Uses X-rays to Detect COVID-19 Rapidly
New artificial intelligence (AI) based test uses X-rays to accurately diagnose COVID-19 quickly.
The testing platform developed by researchers at the University of the West of Scotland (UWS) can detect the SARS-CoV-2 virus far more quickly than a PCR test which typically takes around two hours.

The technology can help relieve strain on hard-pressed hospitals, particularly in countries where PCR tests.

The technique utilizes X-ray technology, comparing scans to a database of around 3000 images belonging to patients with COVID-19, healthy individuals, and people with viral pneumonia.

It used an AI process known as deep convolutional neural network; an algorithm typically used to analyze visual imagery to make a diagnosis.

According to the research published in the journal Sensors, the technique proved to be more than 98 per cent accurate during an extensive testing phase.

"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 from UWS, who led the research.

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"Several countries are unable to carry out large numbers of COVID-19 tests because of limited diagnosis tools, but this technique utilizes easily accessible technology to detect the virus quickly," Ramzan said.

The researchers noted that COVID-19 symptoms are not visible in X-rays during the early stages of infection, so the technology cannot fully replace PCR tests.

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However, it can still play an important role in curtailing the spread of the virus, 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," Ramzan said.

The team now plans to expand the study, incorporating a greater database of X-ray images acquired by different X-ray machines models to evaluate the approach's suitability in a clinical setting

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Source-Medindia


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