A new test powered by artificial intelligence (AI) may be capable of identifying coronavirus within one hour – according to new research.
Its developers say it can rapidly screen people arriving at hospitals for Covid-19 and accurately predict whether or not they have the disease.
Who developed the test?
The Curial AI test has been developed by a team at the University of Oxford and assesses data typically gathered from patients within the first hour of arriving in an emergency department – such as blood tests and vital signs – to determine the chance of a patient testing positive for Covid-19.
What does the test involve?
Currently, testing for the virus involves the molecular analysis of a nose and throat swab, with results having a typical turnaround time of between 12 and 48 hours.
However, the Oxford team said their tool could deliver near-real-time predictions for a patient’s Covid-19 status.
How long has the study been running since?
The study has been running since March, and researchers have tested the AI tool on data from 115,000 visits to A&E at Oxford University Hospitals (OUH).
What have researchers said?
Study lead Dr Andrew Soltan said the tool had accurately predicted a patient’s Covid-19 status in more than 90 per cent of cases, and argued that it could be a useful tool for the NHS.
“Until we have confirmation that patients are negative, we must take additional precautions for patients with coronavirus symptoms, which are very common,” he said.
“The Curial AI is optimised to quickly give negative results with high confidence, safely excluding Covid-19 at the front door and maintaining flow through the hospital.
“When we tested the Curial AI on data for all patients coming to OUH’s emergency departments in the last week of April and the first week of May, it correctly predicted patients’ Covid status more than 90 per cent of the time.”
He added that the researchers now hope to carry out real-world trials of the technology.
“The next steps are to deploy our AI in to the clinical workflow and assess its role in practice,” he said.
“A strength of our AI is that it fits within the existing clinical care pathway and works with existing lab equipment. This means scaling it up may be relatively fast and cheap.
“I hope that our AI may help keep patients and staff safer while waiting for results of the swab test.”
