Science

X-rays combined with AI could help in effective detection of Covid-19: Study

Mumbai | Updated on March 26, 2021

A new study noted that X-rays could be a leading-edge diagnostic tool for Covid-19 patients with the help of artificial intelligence.

According to researchers in Brazil, who taught a computer program, through various machine learning methods combined with chest X-rays are 95.6-98.5 per cent accurate in detecting Covid-19.

The findings of their study were published in IEEE/CAA Journal of Automatica Sinica, a joint publication of the IEEE and the Chinese Association of Automation.

Also read: 7 in 10 Covid-19 patients experience symptoms lingering for months: Study

“When the Covid-19 pandemic arose, we agreed to put our expertise to use to help deal with this new global problem,” said corresponding author Victor Hugo C. de Albuquerque, a researcher in the Laboratory of Image Processing, Signals, and Applied Computing and with the Universidade de Fortaleza.

“We decided to investigate if a Covid-19 infection could be automatically detected using X-ray images,” Albuquerque said.

He noted that most X-ray images are available within minutes, compared to the days required for a swab or saliva diagnostic tests.

However, the researchers also found a lack of publicly available chest X-rays to train their artificial intelligence model to automatically identify the lungs of Covid-19 patients.

So, they used several different machine learning methods, two of which resulted in a 95.6 per cent and a 98.5 per cent accuracy rating, respectively.

Also read: Experts to probe cause of sudden deaths among those vaccinated

“Since X-rays are very fast and cheap, they can help to triage patients in places where the health care system has collapsed or in places that are far from major centers with access to more complex technologies,” Albuquerque said.

“This approach to detect and classify medical images automatically can assist doctors in identifying, measuring the severity and classifying the disease,” he added.

Published on March 26, 2021

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