Oxford deploys AI screening tool for rapid COVID-19 diagnosis

Researchers at the University of Oxford recently published study results on medical preprint server medRxiv detailing their use of artificial intelligence to screen COVID-19 patients.

The research team trained an AI algorithm using clinical data to better triage patients in low-testing environments and identify the infection at the point of care, as standard screening methods often take up to 48 hours to produce a diagnosis. 

Routine blood tests conducted during the patient's arrival, blood gas results and vital signs were used to train the algorithm.

The AI model used for diagnosis among COVID-19-presenting patients in the emergency department resulted in 77 percent sensitivity and 96 percent specificity, while the model used for diagnosis among patients admitted with COVID-19 resulted in 77 percent sensitivity and 95 percent specificity. More than 99 percent of patients the algorithm diagnosed as negative were in fact free of the disease.

Ecditor's note: This article was updated July 14 at 9:00 a.m. CDT. 

More articles on artificial intelligence:
Harvard, Stanford researchers lead COVID-19 AI data initiative: 4 things to know
4 AI systems outperforming medical experts
How UC San Diego Health, AWS implemented an AI imaging algorithm to detect COVID-19 in 10 days

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