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Facebook claims its AI can predict four if a coronavirus patient's condition will deteriorate - Daily Mail

Facebook claims its AI can predict four if a coronavirus patient's condition will deteriorate - Daily Mail

Facebook claims its AI can predict four if a coronavirus patient's condition will deteriorate - Daily Mail
Jan 15, 2021 1 min, 25 secs

Facebook claims to have designed software capable of predicting if a coronavirus patient's health will deteriorate or will need oxygen just by scanning their chest X-rays.

One model is designed to predict deterioration using a single chest X-ray, another does the same but through a series of X-rays and the third uses an X-ray to determine if and how much supplemental oxygen a patient may need.

One model is designed to predict deterioration using a single chest X-ray, another does the same but through a series of X-rays.

The third uses an X-ray to determine if and how much supplemental oxygen a patient may need?

'Our model using sequential chest X-rays can predict up to four days (96 hours) in advance if a patient may need more intensive care solutions, generally outperforming predictions by human experts,' the authors said in a blog post published Friday.

The system was then trained on NYU coronavirus chest X-rays that included a total of 26,383 images from 4,914 patients, which allowed the models to label a patient's condition worsening with 24, 48, 72, or 96 hours of the scan in question.

'Being able to predict whether a patient will need oxygen resources would also be a first, and could help hospitals as they decide how to allocate resources in the weeks and months to come.'.

Facebook claims to have designed software capable of predicting if a coronavirus patient's health will deteriorate or will need oxygen just by scanning their chest X-rays

William Moore, MD, a Professor of Radiology at NYU Langone Health, share in a statement: 'We have been able to show that with the use of this AI algorithm, serial chest radiographs can predict the need for escalation of care in patients with COVID-19.'

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